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Repository: kosukeimai/qss
Branch: master
Commit: 3d6144d4c6fa
Files: 197
Total size: 54.3 MB
Directory structure:
gitextract__a6ivn47/
├── .Rbuildignore
├── .gitignore
├── .travis.yml
├── CAUSALITY/
│ ├── README.md
│ ├── STAR.csv
│ ├── causality-tidy.R
│ ├── causality-tidy.Rmd
│ ├── causality.R
│ ├── causality.Rmd
│ ├── gay.csv
│ ├── leaders.csv
│ ├── minwage.csv
│ ├── resume.csv
│ └── social.csv
├── DESCRIPTION
├── DISCOVERY/
│ ├── README.md
│ ├── constitution.csv
│ ├── discovery-tidy.R
│ ├── discovery-tidy.Rmd
│ ├── discovery.R
│ ├── discovery.Rmd
│ ├── elections.csv
│ ├── federalist/
│ │ ├── fp01.txt
│ │ ├── fp02.txt
│ │ ├── fp03.txt
│ │ ├── fp04.txt
│ │ ├── fp05.txt
│ │ ├── fp06.txt
│ │ ├── fp07.txt
│ │ ├── fp08.txt
│ │ ├── fp09.txt
│ │ ├── fp10.txt
│ │ ├── fp11.txt
│ │ ├── fp12.txt
│ │ ├── fp13.txt
│ │ ├── fp14.txt
│ │ ├── fp15.txt
│ │ ├── fp16.txt
│ │ ├── fp17.txt
│ │ ├── fp18.txt
│ │ ├── fp19.txt
│ │ ├── fp20.txt
│ │ ├── fp21.txt
│ │ ├── fp22.txt
│ │ ├── fp23.txt
│ │ ├── fp24.txt
│ │ ├── fp25.txt
│ │ ├── fp26.txt
│ │ ├── fp27.txt
│ │ ├── fp28.txt
│ │ ├── fp29.txt
│ │ ├── fp30.txt
│ │ ├── fp31.txt
│ │ ├── fp32.txt
│ │ ├── fp33.txt
│ │ ├── fp34.txt
│ │ ├── fp35.txt
│ │ ├── fp36.txt
│ │ ├── fp37.txt
│ │ ├── fp38.txt
│ │ ├── fp39.txt
│ │ ├── fp40.txt
│ │ ├── fp41.txt
│ │ ├── fp42.txt
│ │ ├── fp43.txt
│ │ ├── fp44.txt
│ │ ├── fp45.txt
│ │ ├── fp46.txt
│ │ ├── fp47.txt
│ │ ├── fp48.txt
│ │ ├── fp49.txt
│ │ ├── fp50.txt
│ │ ├── fp51.txt
│ │ ├── fp52.txt
│ │ ├── fp53.txt
│ │ ├── fp54.txt
│ │ ├── fp55.txt
│ │ ├── fp56.txt
│ │ ├── fp57.txt
│ │ ├── fp58.txt
│ │ ├── fp59.txt
│ │ ├── fp60.txt
│ │ ├── fp61.txt
│ │ ├── fp62.txt
│ │ ├── fp63.txt
│ │ ├── fp64.txt
│ │ ├── fp65.txt
│ │ ├── fp66.txt
│ │ ├── fp67.txt
│ │ ├── fp68.txt
│ │ ├── fp69.txt
│ │ ├── fp70.txt
│ │ ├── fp71.txt
│ │ ├── fp72.txt
│ │ ├── fp73.txt
│ │ ├── fp74.txt
│ │ ├── fp75.txt
│ │ ├── fp76.txt
│ │ ├── fp77.txt
│ │ ├── fp78.txt
│ │ ├── fp79.txt
│ │ ├── fp80.txt
│ │ ├── fp81.txt
│ │ ├── fp82.txt
│ │ ├── fp83.txt
│ │ ├── fp84.txt
│ │ └── fp85.txt
│ ├── florentine.csv
│ ├── pres08.csv
│ ├── pres12.csv
│ ├── trade.csv
│ ├── twitter-following.csv
│ ├── twitter-senator.csv
│ └── walmart.csv
├── INTRO/
│ ├── Kenya.csv
│ ├── README.md
│ ├── Sweden.csv
│ ├── UNpop-tidy.R
│ ├── UNpop.R
│ ├── UNpop.RData
│ ├── UNpop.csv
│ ├── UNpop.dta
│ ├── World.csv
│ ├── intro-tidy.R
│ ├── intro-tidy.Rmd
│ ├── intro.R
│ ├── intro.Rmd
│ └── turnout.csv
├── LICENSE
├── MEASUREMENT/
│ ├── README.md
│ ├── USGini.csv
│ ├── afghan-village.csv
│ ├── afghan.csv
│ ├── ccap2012.csv
│ ├── congress.csv
│ ├── gayreshaped.csv
│ ├── measurement-tidy.R
│ ├── measurement-tidy.Rmd
│ ├── measurement.R
│ ├── measurement.Rmd
│ ├── unvoting.csv
│ └── vignettes.csv
├── PREDICTION/
│ ├── MPs.csv
│ ├── README.md
│ ├── face.csv
│ ├── florida.csv
│ ├── intrade08.csv
│ ├── intrade12.csv
│ ├── polls08.csv
│ ├── polls12.csv
│ ├── pollsUS08.csv
│ ├── prediction-tidy.R
│ ├── prediction-tidy.Rmd
│ ├── prediction.R
│ ├── prediction.Rmd
│ ├── pres08.csv
│ ├── pres12.csv
│ ├── progresa.csv
│ ├── social.csv
│ ├── transfer.csv
│ └── women.csv
├── PROBABILITY/
│ ├── FLCensusVTD.csv
│ ├── FLVoters.csv
│ ├── README.md
│ ├── fraud.RData
│ ├── intrade08.csv
│ ├── names.csv
│ ├── pres08.csv
│ ├── probability-tidy.R
│ ├── probability-tidy.Rmd
│ ├── probability.R
│ └── probability.Rmd
├── README.md
├── UNCERTAINTY/
│ ├── MPs.csv
│ ├── README.md
│ ├── STAR.csv
│ ├── chinawomen.csv
│ ├── filedrawer.csv
│ ├── minwage.csv
│ ├── nazis.csv
│ ├── polls08.csv
│ ├── pres08.csv
│ ├── published.csv
│ ├── resume.csv
│ ├── uncertainty-tidy.R
│ ├── uncertainty-tidy.Rmd
│ ├── uncertainty.R
│ ├── uncertainty.Rmd
│ └── women.csv
├── errata/
│ ├── QSS_tidyverse_errata.Rmd
│ └── QSSerrata.Rmd
├── syllabus/
│ ├── README.md
│ ├── RcampPrinceton.tex
│ ├── calendar.sty
│ ├── pol245Princeton.tex
│ └── pol345soc305Princeton.tex
└── test.R
================================================
FILE CONTENTS
================================================
================================================
FILE: .Rbuildignore
================================================
README.md
.git
.gitignore
^\.travis\.yml$
================================================
FILE: .gitignore
================================================
# History files
.Rhistory
.Rapp.history
# Example code in package build process
*-Ex.R
# RStudio files
.Rproj.user/
.DS_Store
================================================
FILE: .travis.yml
================================================
language: r
warnings_are_errors: true
sudo: false
script:
- Rscript test.R
env:
global:
- CRAN: http://cran.rstudio.com
notifications:
email:
on_success: change
on_failure: change
================================================
FILE: CAUSALITY/README.md
================================================
# Chapter 2: Causality
## Code
1. The markdown file for the entire chapter: [causality.Rmd](causality.Rmd) or [causality-tidy.Rmd](causality-tidy.Rmd)
2. The pdf file with outputs: [causality.pdf](causality.pdf) or [causality-tidy.pdf](causality-tidy.pdf)
3. The R script file for the entire chapter: [causality.R](causality.R) or [causality-tidy.R](causality-tidy.R)
## Data sets
### Main text
1. Resume experiment data (Table 2.1): [resume.csv](resume.csv)
2. Social Pressure Experiment Data (Table 2.4): [social.csv](social.csv)
3. Minimum-Wage Study Data (Table 2.5): [minwage.csv](minwage.csv)
### Exercises
1. STAR Project Data (Table 2.6): [STAR.csv](STAR.csv)
2. Gay Marriage Study Data (Table 2.7): [gay.csv](gay.csv)
3. Leader Assassination Data (Table 2.8) [leaders.csv](leaders.csv)
================================================
FILE: CAUSALITY/STAR.csv
================================================
"race","classtype","yearssmall","hsgrad","g4math","g4reading"
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1,1,4,1,686,705
2,2,0,0,NA,NA
1,2,0,1,821,784
1,2,0,1,683,733
1,3,0,NA,702,720
2,2,0,NA,NA,NA
1,2,0,1,NA,NA
2,1,1,NA,NA,NA
1,1,4,NA,NA,NA
1,3,3,1,NA,NA
1,2,0,1,821,767
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,729,763
2,1,2,NA,NA,NA
1,1,4,1,741,740
1,2,0,0,NA,NA
1,2,0,1,758,726
1,1,4,0,640,620
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
2,3,1,NA,NA,NA
2,1,4,NA,678,528
1,2,0,NA,689,648
1,1,3,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,0,706,718
1,2,2,0,708,712
1,1,4,1,744,836
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,1,697,764
1,1,1,NA,NA,NA
1,3,2,1,714,699
2,2,0,NA,NA,NA
1,1,4,1,729,733
1,1,4,1,742,761
1,2,0,NA,NA,NA
1,3,0,1,655,714
1,1,4,NA,NA,NA
1,2,0,NA,NA,NA
1,1,2,NA,699,729
1,2,0,1,NA,NA
1,1,2,0,NA,NA
1,1,2,NA,NA,NA
1,1,4,NA,722,755
2,3,1,NA,732,691
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,716,760
1,3,0,1,740,750
1,3,0,NA,678,722
1,1,3,NA,NA,NA
1,3,0,1,NA,NA
1,1,2,1,NA,NA
1,2,0,NA,550,666
1,3,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,707,747
1,1,4,NA,NA,580
1,2,0,1,758,736
1,1,4,1,701,695
1,1,1,NA,NA,NA
1,2,0,NA,654,634
1,3,0,1,NA,NA
1,1,4,1,739,737
1,3,0,1,694,720
1,1,2,NA,NA,NA
1,3,0,1,720,738
2,2,0,NA,669,674
1,3,0,1,704,714
1,1,4,1,821,756
1,1,4,1,713,781
1,3,0,NA,NA,NA
1,3,0,1,717,782
1,2,0,NA,702,794
1,3,0,NA,700,760
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,NA,NA
2,3,0,NA,NA,NA
1,3,1,1,714,743
1,3,0,NA,714,671
1,2,0,NA,729,836
1,3,0,1,716,737
1,3,0,0,NA,NA
1,1,1,1,728,727
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,1,4,1,747,836
1,2,0,NA,633,673
1,3,1,NA,NA,NA
1,2,0,1,689,671
1,2,0,NA,NA,NA
1,2,0,1,744,836
1,1,2,NA,NA,NA
1,2,0,1,NA,NA
1,2,2,1,693,703
1,2,0,NA,NA,NA
1,3,0,1,737,776
1,1,4,NA,NA,NA
1,2,0,1,NA,NA
1,2,1,1,NA,NA
1,3,0,NA,NA,NA
1,3,2,1,727,751
1,2,0,1,692,778
1,3,0,1,740,698
1,2,0,1,NA,NA
1,3,0,1,696,NA
1,3,0,1,699,NA
1,3,0,0,NA,NA
1,1,4,1,738,NA
1,2,1,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,750,763
1,1,2,1,NA,NA
1,1,3,NA,NA,NA
1,1,4,NA,723,749
2,3,0,1,693,528
1,1,4,1,707,715
1,1,4,1,767,750
1,2,0,NA,NA,NA
1,2,2,1,740,741
2,1,4,NA,687,682
1,3,0,NA,696,760
1,2,0,NA,693,743
1,2,0,1,NA,NA
1,3,0,1,744,761
1,1,4,1,702,741
1,3,3,1,720,702
1,2,0,0,695,696
1,1,1,NA,NA,NA
1,2,0,1,712,740
1,1,4,0,717,741
1,3,0,NA,NA,NA
1,1,4,1,821,796
1,3,3,NA,707,720
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,NA,660,606
1,2,0,1,758,745
1,1,4,0,665,620
1,3,0,1,NA,NA
1,1,2,0,NA,NA
1,2,0,1,740,741
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,741,688
1,2,0,1,NA,NA
1,2,0,1,674,704
1,1,1,1,NA,NA
1,3,0,1,758,734
1,1,1,1,739,836
1,2,0,0,741,753
1,1,2,NA,NA,NA
1,1,1,1,NA,NA
2,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,2,1,821,778
1,1,1,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,1,744,784
1,3,0,NA,NA,NA
1,1,4,0,713,707
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,3,NA,NA,NA
1,2,0,NA,684,794
1,2,0,1,690,728
1,3,3,1,704,719
1,2,0,NA,NA,NA
1,3,2,1,706,737
1,1,4,NA,740,644
2,3,0,NA,NA,NA
2,2,0,1,741,722
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,707,757
2,3,0,NA,NA,NA
1,3,0,1,700,716
1,3,0,NA,487,528
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,741,722
1,3,0,NA,730,763
1,1,1,1,NA,NA
1,2,0,1,704,699
1,1,4,1,715,762
1,2,0,NA,702,716
1,1,4,NA,654,727
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,1,1,1,NA,NA
1,1,4,0,535,705
1,3,0,0,691,717
1,1,1,0,695,741
1,2,0,0,675,721
1,2,3,1,758,769
1,1,2,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,686,742
1,3,0,1,NA,NA
1,1,4,1,758,778
1,3,0,NA,741,782
1,1,1,NA,NA,NA
1,3,0,NA,672,666
1,3,0,NA,NA,NA
1,1,4,NA,758,747
1,3,0,NA,713,785
1,2,0,NA,NA,NA
2,3,0,0,709,713
1,1,4,1,740,785
1,3,0,1,699,756
1,3,0,NA,645,637
1,2,3,1,705,724
1,2,0,NA,NA,NA
1,3,2,1,NA,NA
1,3,0,1,696,673
1,2,3,NA,741,784
2,1,4,1,NA,NA
1,1,4,1,769,761
1,3,0,1,758,751
1,1,4,NA,670,676
1,1,4,NA,714,836
1,1,4,1,758,721
1,2,0,NA,NA,NA
1,3,0,1,767,745
1,3,0,NA,775,796
1,3,3,NA,702,708
1,3,2,1,726,742
1,3,0,1,740,727
1,2,0,NA,699,709
1,2,0,1,739,782
1,3,3,1,750,716
1,1,4,NA,NA,NA
1,1,1,0,NA,NA
1,2,2,0,NA,NA
1,2,0,1,738,742
1,2,0,NA,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,0,1,712,778
1,1,4,1,714,744
1,1,4,1,728,784
1,2,0,NA,758,734
1,1,4,NA,821,710
1,2,0,1,NA,NA
1,2,0,1,758,767
1,1,4,NA,775,728
1,1,3,NA,NA,NA
1,1,4,1,741,784
1,3,0,1,697,706
1,1,4,NA,688,758
1,3,0,1,744,740
1,2,0,NA,645,744
1,2,0,NA,603,669
1,1,1,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,0,NA,NA
1,2,0,NA,691,632
1,2,3,NA,638,528
1,3,0,NA,NA,NA
1,3,0,0,699,723
1,3,0,NA,638,675
1,2,0,1,724,667
1,3,0,NA,NA,NA
1,3,0,NA,711,738
1,3,3,NA,744,629
1,2,0,1,686,698
1,3,3,1,752,716
1,2,0,NA,678,716
1,1,4,1,744,836
2,3,3,1,725,691
1,3,0,1,726,723
1,3,0,1,NA,NA
1,2,0,1,758,763
1,3,0,NA,NA,NA
1,1,3,1,NA,NA
2,1,4,NA,666,674
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,773,741
1,3,0,1,639,701
1,3,0,1,712,704
2,1,1,NA,726,722
1,2,0,0,NA,NA
1,2,0,1,710,736
1,2,0,1,NA,NA
1,2,2,NA,683,715
1,1,3,1,696,757
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,740,778
1,2,0,1,NA,NA
1,1,3,NA,NA,NA
1,3,0,1,719,836
1,3,0,1,NA,NA
1,1,1,1,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,0,771,688
1,1,1,1,NA,NA
1,1,4,0,664,742
1,3,0,1,698,713
1,3,0,1,679,836
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,1,0,NA,NA
1,2,0,1,694,763
1,3,0,1,NA,NA
1,1,4,1,681,704
1,3,0,NA,NA,NA
1,3,0,1,758,741
2,3,0,NA,625,672
2,1,4,NA,659,621
1,1,4,1,744,794
2,3,0,1,726,727
1,2,0,NA,821,763
1,3,0,1,745,700
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,730,736
1,3,0,1,705,659
1,3,1,1,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,741,647
1,3,0,1,NA,NA
1,1,4,NA,758,742
1,1,4,NA,692,759
1,1,4,1,655,709
1,2,0,1,767,760
1,1,4,1,741,735
1,1,4,1,701,740
1,1,4,1,740,741
1,1,4,1,735,761
2,2,0,1,678,681
1,1,2,NA,NA,NA
1,2,0,1,758,760
1,3,0,1,724,721
1,2,0,1,684,622
1,2,0,1,767,765
1,3,0,0,598,736
1,2,0,NA,704,692
1,2,1,1,722,756
1,3,0,1,697,735
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,541,743
1,2,0,1,743,836
1,2,1,1,758,778
1,2,0,1,603,689
1,2,0,NA,709,720
1,3,0,1,744,756
1,2,3,1,749,680
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
1,3,0,1,739,763
1,1,4,1,758,836
1,2,0,1,715,676
1,3,0,1,729,761
2,2,0,NA,NA,NA
1,3,0,1,726,724
1,3,0,NA,NA,NA
1,1,4,NA,666,692
1,3,0,1,717,717
2,1,2,1,NA,NA
1,1,3,1,699,719
1,2,0,1,711,695
1,3,0,1,708,836
1,2,0,0,702,715
1,2,3,1,821,765
1,2,0,1,710,728
1,3,2,1,657,702
1,3,0,1,726,718
1,1,4,1,728,836
2,1,1,0,NA,NA
2,3,0,NA,726,767
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,0,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,0,647,689
2,1,3,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,2,0,0,NA,NA
2,3,0,0,NA,NA
2,2,1,0,NA,NA
2,3,1,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,NA,712,771
1,1,4,1,706,710
1,3,0,1,758,836
1,1,1,NA,NA,NA
1,2,0,1,741,784
1,2,0,NA,743,748
1,2,0,1,662,714
1,2,0,1,715,765
1,2,0,NA,NA,NA
1,1,4,NA,704,724
1,1,2,0,NA,NA
1,3,0,1,NA,NA
1,3,0,1,717,682
1,1,1,1,NA,NA
1,2,0,1,697,604
1,1,3,0,NA,NA
1,2,0,1,658,688
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,1,4,NA,723,732
1,1,3,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,724,734
1,1,1,NA,NA,NA
1,2,0,NA,705,717
1,1,4,1,690,730
1,3,3,1,707,721
1,2,0,NA,732,750
1,3,0,1,709,642
2,3,0,NA,NA,NA
1,1,4,1,698,782
1,2,0,NA,NA,NA
1,3,0,0,719,694
1,1,4,NA,711,751
1,3,0,1,NA,NA
1,1,3,1,NA,NA
1,2,0,1,NA,NA
1,1,2,1,NA,NA
1,3,0,NA,692,738
1,1,4,NA,716,722
1,2,0,1,NA,NA
1,2,0,NA,661,629
1,3,0,0,754,763
1,1,1,NA,NA,NA
1,2,3,1,726,757
1,3,0,1,NA,NA
1,1,4,0,684,731
1,1,4,1,662,632
1,3,0,1,NA,NA
1,1,4,NA,677,723
1,2,0,1,NA,NA
1,2,2,1,771,739
1,2,0,1,664,700
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,0,NA,NA
1,2,0,1,821,705
1,1,1,0,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,718,711
1,3,2,1,691,721
1,3,0,NA,758,750
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,1,3,NA,652,626
1,1,4,1,747,736
1,3,0,0,683,NA
1,3,3,NA,729,NA
1,2,0,0,700,NA
1,2,3,1,726,NA
1,1,4,1,741,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,670,712
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,1,690,711
1,2,3,NA,729,760
1,3,0,1,729,725
1,1,4,NA,719,750
1,1,4,1,703,701
1,1,4,0,699,697
1,2,0,1,648,677
1,2,0,1,717,836
1,1,3,NA,NA,NA
1,2,3,NA,NA,NA
1,3,0,1,744,770
1,2,0,NA,643,646
1,3,3,NA,667,782
1,3,0,1,679,695
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,1,728,760
1,3,0,1,765,745
1,3,0,NA,NA,NA
1,2,0,1,690,695
1,1,4,1,724,737
1,2,1,0,NA,NA
1,1,4,1,758,714
1,3,0,1,769,784
1,3,0,1,NA,NA
1,3,0,NA,767,771
1,1,4,1,686,745
1,2,0,1,716,763
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,0,681,728
1,1,2,1,NA,NA
1,2,0,1,704,668
1,1,4,1,783,836
1,3,0,NA,714,717
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,699,724
1,3,3,NA,739,756
1,1,4,1,636,697
1,1,4,NA,696,794
1,1,1,NA,NA,NA
1,2,0,0,531,641
1,3,0,1,758,760
1,3,0,NA,NA,NA
1,2,0,1,696,688
1,1,4,1,738,685
1,3,0,NA,698,785
1,3,2,NA,NA,NA
1,3,1,1,689,662
1,1,1,NA,NA,NA
1,1,4,NA,704,763
1,2,0,1,696,734
1,2,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,789,750
1,3,0,0,NA,NA
1,1,4,NA,704,725
1,2,0,NA,NA,NA
6,3,0,1,741,778
1,1,4,1,779,782
1,2,0,1,637,691
1,2,0,1,739,771
1,1,4,NA,648,528
1,2,0,0,NA,NA
1,1,4,1,689,705
1,3,0,1,657,705
1,2,0,1,701,652
1,3,0,NA,676,749
1,3,3,1,723,741
2,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,2,3,1,691,763
1,2,0,0,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,715,755
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,676,652
2,3,0,NA,NA,NA
1,3,1,NA,NA,NA
1,1,4,1,679,660
1,3,0,0,NA,NA
1,2,0,NA,736,691
1,2,0,1,NA,NA
1,2,0,1,695,738
1,2,3,0,707,760
1,3,0,0,NA,NA
1,3,0,0,726,692
1,3,0,1,733,703
2,2,0,NA,NA,NA
1,1,2,1,NA,NA
2,2,0,1,707,721
1,1,4,NA,715,715
1,3,0,NA,730,836
1,3,2,NA,695,679
1,3,0,NA,727,689
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,1,727,689
1,2,0,NA,767,750
1,3,0,1,645,683
1,3,0,1,711,753
1,3,0,1,741,686
1,2,0,1,711,751
1,2,0,1,741,724
2,3,0,1,NA,NA
1,1,4,NA,NA,NA
1,1,4,1,741,836
1,2,0,NA,NA,NA
1,1,4,0,672,690
1,2,0,NA,758,741
1,1,4,NA,NA,NA
1,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,728,794
1,1,4,1,708,730
1,3,0,NA,NA,NA
1,3,0,NA,696,699
1,2,0,NA,704,735
1,2,0,1,721,743
1,3,3,NA,716,836
1,1,4,1,744,709
1,3,3,NA,696,707
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,709,699
1,2,0,1,NA,NA
1,2,0,1,702,722
1,1,4,1,758,750
1,2,0,NA,758,676
2,2,0,1,692,740
2,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,752,778
1,3,0,NA,NA,NA
1,3,0,1,694,750
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,821,836
1,3,0,1,754,710
1,1,2,NA,NA,NA
1,2,2,1,696,686
1,2,0,NA,758,717
1,3,0,1,703,702
1,3,3,1,714,751
1,2,0,NA,NA,NA
1,3,1,1,718,685
1,1,4,NA,645,701
1,3,0,NA,NA,NA
1,2,0,NA,769,707
2,3,3,NA,647,564
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,0,711,750
2,1,1,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,672,698
2,3,0,0,NA,NA
2,3,2,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,691,686
1,1,4,NA,682,673
2,2,0,1,736,678
2,1,2,1,NA,NA
2,3,0,NA,NA,NA
2,1,2,0,NA,NA
2,2,0,1,NA,NA
2,1,2,1,731,737
2,1,4,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,711,701
2,3,0,NA,NA,NA
2,1,3,1,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,3,0,NA,NA,NA
2,1,4,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,NA,NA,NA
2,3,1,0,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,1,3,NA,NA,NA
1,3,0,1,724,656
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,0,689,738
1,3,0,1,693,754
1,2,1,1,681,760
1,2,0,1,779,763
1,1,4,1,714,660
1,1,4,NA,NA,NA
1,1,4,NA,694,749
2,2,0,1,NA,NA
1,2,0,NA,702,687
1,2,0,NA,NA,NA
1,2,0,1,703,657
1,2,0,0,NA,NA
1,1,1,1,NA,NA
1,2,1,NA,NA,NA
1,1,4,NA,685,669
1,3,0,1,742,836
1,1,4,1,728,714
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,686,710
1,2,0,1,715,693
1,2,0,NA,731,781
1,1,1,1,NA,NA
1,1,4,NA,NA,NA
1,1,4,1,744,770
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,1,658,673
2,3,0,1,NA,NA
1,3,0,1,712,711
1,1,2,NA,NA,NA
1,3,0,1,694,732
1,2,0,1,744,750
1,3,0,1,719,721
1,2,0,NA,NA,NA
1,1,4,1,652,650
1,2,0,1,699,712
1,2,0,NA,821,836
1,2,0,1,NA,NA
1,2,1,NA,615,637
1,3,0,1,767,735
1,3,1,NA,NA,NA
1,2,0,1,711,748
1,3,2,1,710,794
1,3,0,1,678,760
1,2,0,1,732,749
1,1,4,NA,NA,NA
1,3,0,1,706,711
1,2,0,NA,703,745
1,1,4,NA,726,738
1,1,1,NA,NA,734
1,1,4,1,741,735
1,2,0,1,728,731
2,3,0,1,688,666
1,3,0,NA,730,742
1,3,0,1,717,705
1,1,4,1,728,731
1,1,3,NA,NA,NA
1,1,4,1,708,760
1,1,3,1,724,725
1,2,0,NA,674,740
2,2,0,NA,NA,NA
1,1,4,1,692,690
1,3,0,1,NA,NA
1,2,0,1,691,712
1,1,4,1,744,684
2,1,4,1,741,733
1,1,2,NA,NA,NA
1,2,3,1,685,705
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,3,1,725,836
1,2,0,1,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,3,0,1,725,742
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,1,729,715
2,1,2,1,NA,NA
1,1,3,1,744,739
2,1,4,0,NA,NA
2,1,4,0,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,2,1,NA,NA
2,2,0,NA,NA,NA
2,2,2,NA,NA,NA
2,2,0,NA,NA,NA
2,2,3,1,712,778
2,3,0,NA,693,727
2,2,0,1,NA,NA
1,1,4,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,1,NA,NA
1,1,3,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,633,666
1,1,4,NA,NA,NA
1,1,4,1,738,736
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,NA,639,700
1,3,0,1,821,784
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,4,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,0,NA,NA
3,2,0,NA,731,782
1,1,3,1,NA,NA
2,3,0,0,NA,NA
2,2,3,1,769,736
1,1,4,NA,693,623
1,1,4,1,752,691
1,1,4,NA,NA,NA
1,2,0,0,NA,NA
2,2,0,NA,NA,NA
1,2,2,NA,706,745
1,2,0,NA,632,528
1,2,1,0,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,653,683
1,3,0,NA,687,699
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,1,4,0,707,721
2,1,4,NA,732,733
2,3,1,1,NA,NA
1,3,3,1,714,NA
1,2,0,1,732,700
2,1,4,NA,NA,NA
2,1,2,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,741,714
1,1,1,NA,NA,NA
2,1,4,NA,NA,NA
2,3,0,0,674,707
1,3,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,3,1,736,782
1,2,0,NA,725,744
1,3,0,NA,NA,NA
2,1,3,NA,NA,NA
2,2,2,0,658,698
2,1,4,NA,729,741
1,2,0,0,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,629,703
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,0,NA,NA,NA
1,2,0,0,NA,NA
2,1,4,1,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,687,724
2,3,0,NA,NA,NA
1,1,4,1,679,742
2,3,0,0,NA,NA
1,1,4,1,731,737
1,3,1,1,NA,NA
1,2,0,1,NA,NA
2,2,1,1,NA,NA
2,1,3,1,NA,NA
2,1,3,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,NA,652,708
2,2,0,1,821,778
1,2,0,1,686,750
2,3,0,NA,NA,NA
1,1,4,1,704,722
1,3,0,1,NA,NA
1,1,2,NA,NA,NA
2,1,3,NA,NA,NA
1,2,0,1,758,836
1,1,4,1,724,723
1,3,3,1,721,727
2,2,0,NA,NA,NA
1,1,1,NA,659,689
1,2,0,1,728,750
2,3,0,NA,NA,NA
2,1,4,1,740,760
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,1,728,676
1,1,4,1,821,784
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,648,677
1,3,0,1,726,695
1,3,0,NA,677,748
2,1,4,1,716,720
1,3,0,1,724,737
2,1,4,1,702,699
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,1,1,0,NA,NA
1,2,0,NA,726,785
1,1,4,1,719,836
2,1,4,1,741,729
1,2,0,1,NA,NA
1,1,4,0,NA,NA
1,3,0,NA,741,663
1,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,NA,701,685
1,1,4,1,670,NA
1,3,0,1,NA,NA
2,2,0,0,625,685
2,3,0,1,NA,NA
2,1,4,1,715,696
1,1,4,1,692,744
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,4,NA,730,785
1,3,0,NA,NA,NA
1,2,0,NA,675,710
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,692,696
2,3,0,NA,NA,NA
2,2,0,1,639,635
1,1,1,NA,NA,NA
1,1,4,1,677,740
2,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,2,NA,657,674
2,1,4,1,699,740
1,3,0,NA,NA,NA
2,2,1,NA,NA,NA
2,1,4,1,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,719,764
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,1,1,0,NA,NA
1,3,0,NA,NA,NA
2,1,4,NA,821,778
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,NA,NA
2,3,1,1,758,836
2,2,3,1,NA,NA
2,3,0,0,NA,NA
2,2,0,1,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,0,705,785
1,3,0,1,768,705
1,1,2,1,NA,NA
2,2,0,1,NA,NA
1,1,3,1,667,739
2,1,4,NA,NA,NA
1,2,0,1,728,698
2,1,1,NA,NA,NA
2,2,0,NA,671,586
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,691,716
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,0,NA,700,688
2,3,2,1,NA,NA
2,2,0,NA,731,695
1,1,4,1,715,683
1,3,0,1,755,690
2,1,3,NA,NA,NA
1,2,0,1,NA,NA
2,1,4,NA,707,671
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,1,688,689
1,1,4,NA,705,682
2,3,3,0,680,721
2,3,0,1,758,722
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,4,1,717,723
1,2,3,NA,NA,NA
2,2,1,1,696,648
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,0,0,NA,NA
2,1,4,NA,742,836
2,3,0,NA,705,647
2,3,0,NA,NA,NA
2,1,2,NA,NA,NA
2,3,0,1,NA,NA
2,1,4,1,655,700
2,1,4,1,711,692
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,3,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,2,1,NA,NA
2,2,0,1,NA,NA
1,1,3,1,NA,NA
1,3,0,NA,726,727
2,2,0,NA,NA,NA
1,2,0,0,NA,NA
1,3,0,1,758,733
1,3,0,1,821,742
1,1,1,1,NA,NA
1,1,4,1,627,702
1,2,1,1,709,741
1,1,2,1,NA,NA
2,1,3,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,NA,NA,NA
1,1,4,1,668,528
2,3,0,NA,668,589
1,2,0,1,690,688
1,3,0,1,821,836
2,1,4,0,702,737
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,4,1,821,836
2,3,0,0,NA,NA
2,1,3,1,NA,NA
2,2,0,0,NA,NA
1,1,3,0,NA,NA
2,2,0,1,758,715
1,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,661,695
2,1,2,1,NA,NA
1,3,0,1,738,762
2,2,0,NA,706,719
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,767,728
1,1,4,NA,734,794
1,2,0,0,667,744
1,2,0,NA,NA,NA
2,1,3,NA,NA,NA
1,2,0,NA,NA,NA
1,2,2,1,758,750
1,2,0,NA,539,528
1,3,0,1,NA,NA
2,1,1,NA,NA,NA
1,1,2,NA,NA,NA
2,3,0,NA,709,727
2,2,0,NA,NA,NA
2,3,0,1,733,684
1,1,4,1,693,680
1,3,0,0,NA,NA
2,3,0,1,NA,NA
1,1,4,1,702,714
2,2,0,NA,NA,NA
1,2,0,1,691,699
1,2,0,1,NA,NA
1,1,4,1,706,730
1,3,0,1,NA,NA
1,1,4,0,663,677
2,3,0,1,NA,NA
1,3,0,1,708,731
1,2,2,1,689,717
2,3,0,NA,NA,NA
2,1,1,1,687,NA
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,NA,NA,NA
1,1,2,1,715,689
1,1,2,NA,NA,NA
1,1,3,NA,NA,NA
2,3,1,1,NA,NA
2,3,1,0,NA,NA
1,2,3,NA,744,724
1,3,0,1,741,682
1,3,3,1,733,760
1,2,0,1,704,731
2,2,0,NA,NA,NA
1,2,0,1,744,760
1,3,0,NA,697,782
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,1,740,750
1,1,4,1,758,742
2,1,4,NA,NA,NA
1,3,3,1,710,741
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,727,767
2,1,1,NA,NA,NA
1,2,2,0,659,728
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,758,836
1,1,4,NA,NA,NA
1,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,1,3,NA,NA,NA
2,3,1,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,1,736,717
1,1,1,NA,NA,NA
1,1,4,NA,NA,NA
1,1,2,NA,NA,NA
1,2,2,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
2,1,4,NA,731,686
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,1,3,NA,NA,NA
2,1,3,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,1,NA,NA
2,1,1,NA,NA,NA
2,3,1,1,700,634
1,3,1,0,NA,NA
1,3,0,1,NA,NA
1,1,1,1,NA,NA
2,2,0,0,NA,NA
2,2,0,1,738,642
1,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,NA,701,672
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,4,1,690,701
2,3,0,NA,NA,NA
1,2,0,NA,667,651
1,2,0,1,707,758
1,3,0,1,667,700
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,698,720
1,3,0,1,NA,NA
1,1,2,1,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,821,836
1,3,0,1,742,763
1,2,0,1,729,695
2,1,4,1,NA,NA
1,2,0,NA,665,681
1,2,0,0,NA,NA
1,1,3,0,758,707
2,3,2,NA,651,710
1,2,0,1,664,725
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,1,3,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
2,1,4,NA,698,660
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,1,4,1,683,701
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,1,1,702,734
1,1,4,NA,692,678
1,1,3,NA,NA,NA
1,2,0,NA,741,782
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,1,4,1,725,730
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,1,4,NA,650,662
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,729,712
1,1,4,NA,711,661
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,1,1,1,NA,NA
1,1,2,1,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,686,699
1,2,0,NA,678,699
1,3,0,NA,NA,NA
1,3,1,NA,758,731
2,2,3,NA,NA,NA
1,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,1,693,669
1,2,0,1,696,720
1,1,4,1,701,686
1,1,4,1,710,694
1,3,0,NA,NA,NA
1,1,1,0,NA,NA
2,2,3,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,720,691
1,3,0,1,NA,NA
1,3,0,NA,717,571
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
3,3,0,1,718,726
2,2,0,NA,680,712
2,3,0,0,NA,NA
1,3,0,NA,NA,NA
1,3,3,NA,NA,NA
2,1,4,0,677,700
1,1,1,NA,NA,NA
1,3,0,NA,738,760
2,3,3,1,NA,NA
1,1,4,1,NA,NA
2,3,0,1,747,719
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,3,NA,NA,NA
2,1,3,1,734,718
2,3,0,1,705,528
1,1,1,1,739,760
2,1,2,1,NA,NA
1,3,0,1,744,716
2,3,0,NA,NA,NA
1,2,0,1,731,757
1,1,4,1,758,708
1,3,0,1,742,771
2,3,0,NA,NA,NA
1,3,0,1,648,615
1,2,0,NA,NA,NA
2,1,4,NA,713,717
1,2,0,1,NA,NA
2,1,3,NA,NA,NA
1,1,2,1,NA,NA
1,1,4,NA,NA,NA
1,3,0,1,741,836
2,3,3,0,702,598
1,2,0,1,767,760
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,1,NA,NA
1,1,4,1,NA,NA
1,2,0,1,NA,NA
2,1,3,1,NA,NA
2,1,4,1,NA,NA
2,3,0,1,NA,NA
1,3,0,1,758,703
1,3,0,1,692,705
2,1,3,1,NA,NA
1,3,0,NA,NA,NA
2,2,0,1,742,672
2,2,2,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,3,0,1,697,669
1,3,0,1,744,750
2,3,0,0,NA,NA
1,1,1,NA,NA,NA
2,1,4,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
2,1,4,1,689,650
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,2,NA,NA,NA
2,2,1,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,651,612
2,2,0,NA,NA,NA
2,1,4,NA,758,760
1,2,0,1,NA,NA
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
1,2,0,1,682,719
2,1,2,NA,NA,NA
2,2,3,NA,NA,NA
2,1,3,NA,NA,NA
2,1,3,NA,NA,NA
2,2,0,0,NA,NA
2,2,0,1,NA,NA
2,1,3,1,NA,NA
2,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,0,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,1,0,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
1,1,2,1,NA,NA
2,2,0,1,NA,NA
2,1,1,NA,NA,NA
1,1,1,1,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,727,750
2,1,4,NA,NA,NA
1,3,0,NA,629,621
2,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,1,NA,NA
1,3,3,1,669,767
2,2,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
2,2,0,1,NA,NA
2,2,0,1,NA,NA
2,2,2,1,NA,NA
1,3,0,NA,NA,NA
2,2,1,1,NA,NA
2,3,1,NA,NA,NA
2,1,4,1,732,750
2,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,1,677,689
2,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,3,NA,NA,NA
1,3,0,NA,700,671
2,2,1,NA,NA,NA
2,1,2,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,1,691,722
2,2,0,NA,NA,NA
1,3,3,1,725,836
1,3,0,1,686,719
2,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,4,1,741,763
1,3,2,1,709,836
2,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,2,0,0,NA,NA
1,2,1,1,NA,NA
2,3,0,0,700,688
1,1,4,1,741,785
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,739,836
2,2,0,0,NA,NA
2,3,0,1,686,679
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
2,1,1,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
2,3,0,1,712,670
1,3,2,1,702,710
1,2,3,NA,NA,NA
1,3,0,1,731,722
1,2,0,NA,NA,NA
2,3,1,NA,NA,NA
1,2,0,1,736,752
2,2,0,1,NA,NA
1,3,0,1,711,763
1,1,4,1,706,657
2,3,1,1,NA,NA
1,2,0,NA,NA,NA
2,1,2,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,662,691
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,668,734
2,2,0,1,NA,NA
1,1,4,NA,NA,NA
1,1,3,1,NA,NA
1,2,0,1,714,761
1,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,704,836
1,2,0,NA,740,724
2,1,4,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,708,614
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,1,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,682,711
2,3,0,1,487,589
1,2,1,NA,690,741
1,3,0,1,698,719
1,3,3,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,1,725,836
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,3,1,NA,NA
1,2,0,1,752,709
2,1,4,NA,692,706
2,3,0,NA,NA,NA
1,1,4,1,NA,NA
2,3,0,0,671,745
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,3,NA,NA,NA
1,1,4,NA,739,712
2,2,0,NA,NA,NA
1,1,4,NA,695,694
1,3,0,NA,634,796
1,2,0,NA,705,720
2,1,4,1,622,708
1,1,4,1,821,763
2,2,0,NA,NA,NA
1,2,0,1,739,730
2,3,2,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,1,0,NA,NA
2,2,0,NA,NA,NA
2,1,2,1,NA,NA
1,1,3,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,696,687
2,1,4,NA,NA,NA
1,1,4,1,NA,NA
1,3,2,1,769,741
1,1,4,1,708,731
1,3,0,NA,677,NA
1,3,0,NA,NA,NA
1,2,0,1,682,725
1,3,0,1,741,740
1,1,4,NA,706,NA
1,3,0,1,821,NA
1,3,0,1,711,NA
1,2,0,NA,720,NA
1,2,0,NA,685,627
1,1,4,NA,692,706
1,1,4,1,732,677
1,3,0,0,685,NA
1,2,0,1,695,715
1,1,3,NA,NA,NA
1,1,4,NA,726,NA
1,2,0,0,NA,NA
1,3,0,1,NA,NA
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,726,750
2,2,1,1,NA,NA
1,1,3,1,NA,NA
1,3,0,1,648,724
2,3,0,NA,NA,NA
1,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,1,NA,NA
1,1,4,NA,711,646
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,2,1,0,NA,NA
1,2,0,NA,NA,NA
1,2,2,NA,769,736
1,3,2,NA,661,689
1,2,0,1,NA,NA
1,2,0,1,699,732
1,3,0,NA,NA,NA
1,1,4,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,741,670
1,3,3,1,750,796
2,3,0,NA,NA,NA
2,1,1,1,NA,NA
1,2,0,0,640,662
2,2,0,1,NA,NA
1,1,4,NA,689,731
2,1,4,1,706,731
1,1,4,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,758,711
2,3,0,NA,NA,NA
1,3,0,1,698,723
2,3,0,NA,NA,NA
1,2,0,0,736,745
2,3,0,1,NA,NA
2,2,0,1,NA,NA
1,3,0,1,NA,NA
1,2,0,1,707,722
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,1,1,0,NA,NA
1,1,3,NA,NA,NA
2,3,0,1,661,676
1,1,2,1,NA,NA
1,3,3,NA,686,637
2,3,0,NA,NA,NA
2,1,2,0,NA,NA
1,2,0,0,NA,NA
1,3,0,1,NA,NA
1,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,1,744,760
1,3,0,NA,NA,NA
1,2,0,1,677,724
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,4,1,688,703
1,3,0,1,670,528
1,2,0,NA,739,756
2,3,0,NA,NA,NA
1,3,0,NA,765,836
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,1,NA,NA
2,1,2,NA,NA,NA
1,2,0,1,821,731
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,1,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,727,770
1,2,3,1,720,744
2,3,0,1,702,691
2,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,2,NA,NA,NA
2,3,0,1,NA,NA
1,1,4,1,738,836
2,3,0,NA,NA,NA
2,3,0,1,717,771
1,1,4,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,738,718
1,2,3,NA,758,836
2,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,758,742
2,3,0,1,NA,NA
2,1,2,NA,NA,NA
2,1,1,0,NA,NA
2,3,0,0,NA,NA
2,1,1,NA,NA,NA
2,2,0,0,664,708
2,2,0,1,NA,NA
1,2,0,1,719,736
2,1,1,NA,NA,NA
2,2,0,0,NA,NA
1,3,0,1,821,778
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,1,4,NA,NA,NA
2,2,0,1,NA,NA
2,3,1,NA,NA,NA
2,1,3,0,NA,NA
2,2,0,1,704,651
1,3,0,NA,NA,NA
1,3,0,0,689,722
1,3,0,NA,757,711
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,0,NA,NA
1,1,1,0,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,NA,NA
1,3,0,1,699,692
2,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,3,1,1,821,748
1,1,1,NA,NA,NA
2,3,1,1,719,701
2,3,0,NA,NA,NA
2,1,2,1,758,696
2,2,0,1,715,734
2,2,0,1,NA,NA
1,2,0,NA,706,778
2,2,0,1,721,687
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
2,3,1,NA,NA,NA
2,3,0,1,NA,NA
1,1,2,1,758,718
2,3,0,NA,NA,NA
2,3,0,0,NA,NA
1,3,0,1,727,782
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,693,750
2,3,0,NA,NA,NA
1,1,4,1,758,702
1,2,0,NA,726,719
2,1,1,1,NA,NA
2,3,0,NA,532,640
1,2,0,NA,NA,NA
2,2,0,0,NA,NA
2,2,2,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,3,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,1,3,0,NA,NA
2,1,4,1,696,NA
1,2,0,NA,NA,NA
1,1,4,1,NA,NA
1,3,0,0,NA,NA
2,3,0,NA,707,836
1,3,0,NA,704,700
1,1,4,1,695,794
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
1,1,1,1,NA,NA
1,3,0,1,758,751
2,2,0,1,NA,NA
1,1,4,1,729,756
1,2,3,1,728,729
1,3,0,NA,NA,NA
1,1,4,1,741,722
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
1,3,0,1,683,739
2,3,1,NA,NA,NA
1,2,0,0,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,666,682
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,3,1,NA,836
1,2,0,1,715,836
1,2,0,NA,704,709
1,3,0,1,711,742
2,3,0,1,NA,NA
1,3,0,NA,721,765
1,2,0,1,675,665
1,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,0,732,716
1,3,0,1,703,733
1,3,1,1,674,697
1,2,0,1,716,683
1,3,0,1,758,751
2,2,0,0,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
1,3,0,NA,639,699
1,2,2,NA,670,528
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,1,NA,725,709
1,3,0,1,729,741
1,2,0,1,729,752
2,2,0,1,701,718
1,3,0,1,742,836
2,2,1,1,NA,NA
2,1,4,1,NA,NA
1,3,0,1,706,726
1,2,0,0,715,776
1,2,0,1,749,708
2,3,0,NA,679,659
2,3,0,1,716,718
1,1,4,1,686,703
1,2,0,1,741,750
1,1,4,1,694,731
2,2,0,NA,NA,NA
1,2,0,NA,713,741
1,3,0,1,696,706
1,2,1,1,773,723
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,1,1,715,661
1,1,4,1,679,707
1,1,4,1,727,702
2,1,1,NA,NA,NA
2,1,4,1,679,734
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,4,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,676,760
1,3,0,1,NA,NA
1,1,4,0,767,735
2,1,3,NA,NA,NA
1,2,1,1,NA,NA
1,1,4,NA,744,720
1,3,0,1,661,656
1,3,0,1,NA,NA
1,3,0,1,769,756
1,3,0,1,705,718
1,1,4,1,742,760
1,2,0,1,710,717
1,3,0,NA,NA,NA
1,2,0,NA,667,740
1,3,1,1,758,836
1,3,0,1,768,760
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,1,4,1,741,717
2,1,2,NA,NA,NA
1,2,0,1,724,732
1,2,0,1,704,735
1,3,0,1,629,528
2,3,0,NA,NA,NA
1,3,0,NA,693,716
2,3,0,1,725,699
2,2,0,NA,NA,NA
1,2,0,1,711,699
1,2,0,1,707,725
2,3,3,NA,638,666
1,1,4,1,766,836
1,2,0,1,NA,NA
1,1,1,NA,NA,NA
2,2,0,1,NA,NA
1,2,2,1,707,728
2,3,2,1,723,720
1,1,4,NA,727,736
2,1,4,NA,722,745
2,1,3,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,NA,NA
2,2,0,1,692,720
2,1,4,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
3,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,0,NA,NA
2,3,0,1,732,760
1,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,0,NA,NA
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,2,1,NA,NA
2,1,3,NA,672,591
1,3,0,1,710,702
2,3,3,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,0,NA,NA
2,3,0,NA,NA,NA
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,1,4,1,749,761
2,2,0,0,NA,NA
2,3,0,NA,626,710
2,2,0,1,NA,NA
1,2,0,NA,692,668
1,2,0,1,709,693
2,1,2,NA,NA,NA
1,1,1,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,0,719,655
2,2,0,NA,NA,NA
2,3,0,1,725,691
2,2,0,NA,NA,NA
2,1,1,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,685,689
2,1,2,NA,NA,NA
2,1,3,NA,NA,NA
2,2,1,1,NA,NA
1,3,0,0,NA,NA
2,3,1,NA,NA,NA
2,3,1,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,4,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,2,2,1,821,722
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,3,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,671,699
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,2,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,2,NA,NA,NA
2,3,1,NA,NA,NA
3,2,2,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,689,655
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,704,708
1,3,0,NA,NA,NA
1,3,0,1,717,721
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,626,692
1,3,0,NA,NA,NA
1,1,4,1,709,703
1,2,0,1,700,689
2,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,698,760
1,1,4,NA,710,763
1,2,1,1,NA,NA
1,2,0,1,NA,NA
1,1,4,1,726,771
1,2,0,1,676,586
1,2,0,1,729,743
1,2,0,1,689,740
2,2,0,0,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,1,NA,NA,NA
2,1,2,NA,NA,NA
2,3,1,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,672,593
2,2,1,NA,NA,NA
2,3,3,NA,NA,NA
2,1,3,1,NA,NA
1,1,4,1,821,755
2,1,3,NA,NA,NA
2,2,0,1,NA,NA
1,1,4,1,640,702
1,1,2,NA,NA,NA
1,1,4,1,653,689
1,3,0,1,758,836
1,3,0,NA,NA,NA
1,1,4,0,712,742
1,3,0,1,709,758
2,2,0,0,NA,NA
2,2,0,1,711,707
1,2,0,NA,719,735
2,3,0,NA,NA,NA
1,2,0,1,704,724
1,3,0,1,683,670
1,2,0,1,NA,NA
2,1,1,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,0,NA,NA
1,2,0,0,705,732
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,758,750
1,2,0,1,709,757
1,2,0,1,733,708
1,3,0,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,NA,741,763
2,1,1,NA,NA,NA
2,3,0,0,NA,NA
1,2,0,1,758,760
1,1,4,NA,721,713
1,2,1,NA,NA,NA
1,2,0,1,740,746
2,2,0,NA,729,721
1,1,4,1,735,750
2,1,2,NA,NA,NA
1,3,0,1,740,701
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,703,723
1,3,0,1,NA,NA
1,2,0,1,715,722
2,3,2,1,NA,NA
2,3,1,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,1,821,784
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,1,NA,NA,NA
1,3,0,1,NA,NA
2,1,4,NA,NA,NA
2,2,0,1,NA,NA
1,1,4,NA,672,683
1,2,0,NA,NA,NA
1,1,4,1,NA,NA
1,2,0,1,NA,NA
1,3,3,1,487,600
1,1,4,NA,NA,NA
1,1,4,NA,741,836
2,3,0,NA,NA,NA
2,2,0,0,NA,NA
1,1,1,1,NA,NA
1,2,0,1,704,711
2,1,1,NA,NA,NA
1,3,0,1,725,768
2,2,0,NA,NA,NA
2,1,4,1,682,613
1,2,0,1,NA,NA
2,2,1,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,0,NA,NA
1,3,3,NA,NA,NA
2,2,0,NA,NA,NA
2,2,3,NA,635,690
2,2,0,0,NA,NA
2,1,4,1,NA,NA
2,1,4,1,NA,NA
1,2,0,1,700,713
1,1,2,0,671,701
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,1,1,NA,744,760
1,3,0,1,720,745
1,3,0,1,726,750
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,2,1,NA,NA
1,3,2,1,821,778
1,2,0,NA,NA,NA
1,1,4,1,636,NA
1,3,0,NA,741,736
1,1,1,1,688,NA
1,3,0,NA,NA,NA
1,1,4,0,684,698
1,3,0,1,668,NA
1,2,0,0,NA,NA
1,3,0,1,744,733
1,2,0,1,740,836
1,2,0,1,821,745
1,1,4,1,693,NA
1,2,0,NA,NA,NA
1,3,0,1,711,784
1,1,4,0,729,712
1,3,0,0,NA,NA
1,1,4,1,767,782
1,2,0,NA,NA,NA
1,1,4,1,741,749
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,4,1,678,699
1,1,1,1,NA,NA
2,3,0,1,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,1,685,736
1,3,0,1,680,731
1,1,4,1,703,629
2,1,4,1,672,684
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,741,647
2,1,4,1,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,1,4,NA,727,724
1,3,0,NA,NA,NA
2,1,4,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,1,NA,NA
2,1,1,NA,NA,NA
1,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,2,3,1,714,698
1,3,0,1,721,528
2,1,2,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,0,NA,NA
2,2,0,NA,NA,NA
1,1,4,NA,672,782
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,699,724
2,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,775,836
2,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,723,705
1,1,4,NA,775,738
2,2,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,1,691,734
1,3,0,1,768,785
2,2,2,1,771,685
2,2,0,NA,NA,NA
1,3,0,1,758,737
1,1,4,0,NA,NA
1,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,3,0,0,NA,NA
2,1,2,NA,NA,NA
2,2,0,1,NA,NA
2,1,2,1,NA,NA
1,2,0,1,679,740
1,2,0,NA,NA,NA
2,3,0,1,NA,NA
1,3,0,1,728,752
1,2,0,1,768,747
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,1,NA,NA
2,1,2,NA,NA,NA
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,635,528
1,2,0,0,705,696
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,728,727
1,2,0,NA,670,750
1,3,0,1,702,750
1,3,0,0,741,718
1,2,0,1,679,836
1,2,2,NA,717,769
1,2,0,NA,639,641
1,3,0,1,NA,NA
1,2,0,1,739,747
1,1,2,NA,NA,NA
1,1,2,NA,729,703
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,737,756
1,2,0,1,717,836
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
2,2,0,1,687,700
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,769,760
2,3,0,NA,NA,NA
1,2,0,1,712,680
2,2,0,NA,706,738
2,3,0,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,1,4,0,570,621
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,NA,700,713
2,2,0,1,NA,NA
1,1,2,0,NA,NA
1,1,4,1,744,778
1,3,0,1,674,736
1,3,0,1,758,729
2,2,0,1,NA,NA
1,2,0,0,717,667
1,2,0,NA,758,736
2,3,0,NA,683,704
1,1,4,1,733,691
1,2,0,1,648,705
1,2,0,NA,NA,NA
2,1,3,1,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,3,NA,NA,NA
1,1,4,NA,674,681
1,2,0,1,NA,NA
2,1,3,NA,NA,NA
2,3,2,NA,NA,NA
2,2,0,NA,NA,NA
2,1,4,0,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,1,NA,NA
1,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,2,1,608,666
2,2,0,NA,NA,NA
1,1,4,NA,NA,NA
2,3,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,0,NA,NA
1,3,0,NA,675,716
1,3,0,0,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,547,528
1,2,0,NA,738,732
2,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,0,668,687
1,2,0,NA,NA,NA
1,3,0,1,677,778
1,2,0,1,690,692
1,2,3,1,740,782
1,3,0,NA,NA,NA
1,2,0,1,685,650
1,1,1,NA,NA,NA
1,3,0,1,726,693
1,2,0,1,716,760
1,2,0,NA,713,723
1,3,0,1,NA,NA
1,1,4,NA,725,688
1,3,0,NA,726,769
1,1,4,1,710,734
1,2,0,NA,705,732
1,2,0,NA,725,679
1,2,0,NA,652,693
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
2,3,1,1,701,528
2,2,0,1,727,694
2,2,0,1,676,692
1,3,0,0,NA,NA
1,1,4,1,690,725
1,3,0,1,628,575
1,1,4,1,680,653
1,3,3,0,734,772
1,2,1,0,NA,NA
2,1,4,NA,678,679
1,2,0,0,NA,NA
1,3,0,1,NA,NA
1,1,2,0,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,712,712
1,2,0,NA,725,700
1,2,1,1,726,794
2,1,1,1,NA,NA
1,1,2,1,NA,NA
1,2,1,1,694,688
1,2,0,1,718,760
1,1,2,NA,NA,NA
2,1,4,1,693,734
1,2,0,1,NA,NA
2,2,0,NA,NA,NA
1,1,4,NA,717,836
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,717,753
1,3,0,1,701,723
1,3,0,0,NA,NA
1,2,0,1,622,727
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
1,2,0,1,741,746
1,3,0,1,681,720
1,2,0,1,694,674
2,1,1,NA,NA,NA
1,3,0,1,715,698
1,3,0,1,699,739
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,741,778
1,1,4,1,726,755
1,2,0,1,NA,NA
1,2,0,0,688,745
1,3,0,NA,NA,NA
1,2,0,0,685,719
1,3,0,NA,708,699
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,0,695,720
1,2,0,1,688,734
1,3,0,1,690,689
1,3,0,1,677,763
1,3,0,1,NA,NA
1,3,2,1,721,728
1,1,2,0,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,2,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,679,760
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,3,0,0,717,728
2,2,0,1,NA,NA
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,1,1,NA,NA
2,2,0,NA,742,752
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,1,4,1,821,769
2,2,0,1,NA,NA
1,1,4,1,701,738
2,1,2,0,NA,NA
2,2,0,1,711,769
2,2,0,NA,666,672
2,3,3,NA,695,724
1,1,1,NA,NA,NA
1,2,0,1,758,731
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
1,1,2,NA,668,724
1,1,2,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,694,711
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,641,697
1,1,4,1,691,635
1,1,4,1,689,721
1,2,0,1,NA,NA
1,1,1,1,NA,NA
1,1,4,NA,744,733
2,2,0,NA,NA,NA
1,3,0,1,758,727
1,1,3,NA,NA,NA
1,2,0,1,730,667
1,1,4,1,700,705
1,1,4,1,703,723
1,3,0,1,NA,NA
1,3,0,1,671,713
2,3,0,NA,NA,NA
1,2,0,1,679,689
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,3,1,714,724
1,2,0,1,NA,NA
2,3,0,1,NA,NA
1,2,0,1,715,739
1,2,0,1,752,714
2,3,0,NA,NA,NA
1,3,0,NA,715,706
1,1,3,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,728,750
1,2,0,NA,NA,NA
1,2,0,1,758,836
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,758,784
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,1,4,1,690,707
2,3,0,NA,NA,NA
1,2,0,1,719,710
1,1,1,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,NA,NA,NA
1,3,1,1,NA,NA
1,1,4,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,NA,736,836
1,2,0,1,740,836
1,1,2,1,NA,NA
1,1,1,1,NA,NA
1,1,4,1,NA,NA
1,3,0,1,700,756
1,2,0,1,743,685
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,758,NA
1,3,0,1,767,NA
1,1,1,NA,NA,NA
1,2,0,1,713,NA
1,1,4,1,753,745
2,2,0,NA,707,682
1,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,680,718
1,1,4,1,695,734
1,2,3,1,716,721
1,2,0,1,735,836
1,2,0,NA,741,672
1,3,0,1,693,685
1,2,0,NA,758,725
1,1,4,1,NA,NA
1,2,0,NA,696,693
1,1,4,NA,747,734
2,1,1,NA,NA,NA
1,1,4,NA,724,665
1,3,0,NA,NA,NA
2,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,3,NA,NA,NA
2,2,3,1,705,707
2,3,0,NA,683,697
1,3,0,NA,NA,NA
1,1,1,NA,666,667
2,3,0,NA,NA,NA
2,3,1,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,716,690
1,3,0,NA,704,714
1,1,4,0,697,713
1,2,0,NA,706,760
1,3,0,1,NA,NA
1,3,0,NA,671,616
2,2,0,NA,704,669
2,3,0,NA,NA,NA
1,3,0,NA,723,718
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,1,713,744
1,1,4,NA,688,731
1,3,0,0,NA,NA
1,1,4,1,684,685
1,2,0,1,NA,NA
1,1,4,1,728,750
1,1,4,1,726,709
1,3,0,1,725,735
1,1,3,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,0,NA,NA
1,1,4,1,NA,NA
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
1,1,4,NA,720,741
2,3,0,1,NA,NA
2,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,718,693
1,3,0,NA,707,760
1,3,0,NA,765,836
2,2,0,0,NA,NA
1,2,0,1,684,719
1,2,0,NA,NA,NA
1,3,0,1,720,678
1,2,0,1,727,747
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,1,4,1,719,750
1,1,2,1,NA,NA
1,2,0,1,NA,NA
1,2,0,1,758,781
1,2,0,NA,717,701
1,3,0,1,694,702
1,1,1,1,NA,NA
1,2,0,NA,740,713
1,1,2,NA,NA,NA
1,2,3,NA,NA,NA
1,2,0,1,732,688
1,2,0,1,758,695
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,664,717
1,1,1,1,NA,NA
1,3,0,1,758,745
1,1,4,NA,679,720
1,1,4,NA,758,763
1,3,0,1,739,782
1,3,0,1,NA,NA
1,2,0,1,712,730
1,1,4,1,769,771
1,2,0,NA,NA,NA
1,2,3,1,704,741
1,1,1,NA,NA,NA
1,3,0,NA,585,667
1,3,0,0,487,668
1,3,0,NA,NA,NA
1,1,2,0,NA,NA
1,1,2,1,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,727,736
1,2,0,NA,NA,NA
1,3,0,NA,671,700
1,1,4,1,686,734
1,3,0,NA,726,836
1,1,4,0,722,836
1,1,4,1,681,725
1,1,2,1,NA,NA
1,2,0,1,690,730
1,2,0,1,703,680
2,2,0,1,707,670
1,3,0,NA,NA,NA
2,1,1,1,639,656
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,1,708,740
3,2,0,NA,723,756
3,2,0,1,704,684
1,3,0,1,664,687
1,2,0,NA,821,719
1,1,4,1,NA,NA
1,3,0,NA,724,746
1,1,1,NA,NA,NA
1,1,4,1,666,721
1,2,0,1,752,754
1,1,4,1,679,727
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,3,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,723,757
1,3,0,1,756,NA
2,3,0,0,668,675
2,3,0,NA,NA,NA
2,1,4,NA,554,610
1,2,1,0,NA,NA
2,1,4,NA,693,718
2,2,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,1,4,1,740,778
1,3,0,0,NA,NA
1,1,4,1,676,717
1,3,0,1,661,700
1,3,0,1,725,714
1,2,0,NA,NA,NA
1,2,0,1,738,836
1,2,1,1,677,698
1,2,0,1,643,724
1,3,0,1,821,782
1,2,0,1,NA,NA
1,2,0,1,658,699
1,2,0,0,NA,NA
1,2,0,0,709,696
1,2,0,0,707,697
2,2,0,NA,NA,NA
1,1,4,NA,758,836
2,3,2,1,731,715
1,3,0,1,789,729
1,2,0,1,NA,NA
1,3,0,1,730,701
1,3,0,1,717,683
1,2,0,1,707,726
1,3,0,1,773,724
1,3,0,1,NA,NA
1,3,0,NA,724,763
1,2,1,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,821,721
1,1,3,1,NA,NA
2,2,0,1,NA,NA
2,3,1,1,723,686
2,3,0,NA,NA,NA
1,2,0,0,NA,NA
1,2,0,1,701,696
1,2,0,1,744,716
2,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,1,1,1,NA,NA
2,2,0,1,639,620
1,1,1,NA,NA,NA
2,2,0,NA,711,744
1,2,0,NA,683,644
1,1,4,NA,705,686
1,3,0,NA,668,706
1,3,0,NA,NA,NA
1,1,3,1,NA,NA
1,1,4,NA,691,667
2,2,0,NA,NA,NA
1,1,4,NA,718,739
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,821,763
1,3,0,1,704,718
1,3,0,1,749,733
1,2,0,1,NA,NA
1,2,0,1,744,771
1,3,0,NA,NA,NA
1,1,1,1,727,737
1,3,1,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,674,713
1,1,4,1,766,743
1,2,0,NA,692,677
1,1,2,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,701,698
1,3,0,1,NA,NA
1,1,3,0,NA,NA
1,3,0,1,734,731
1,2,0,1,741,741
1,1,4,NA,711,707
1,2,3,1,705,776
1,2,0,1,742,741
1,1,4,1,707,719
1,1,1,1,NA,NA
1,2,2,1,775,722
1,3,0,NA,651,NA
1,3,0,NA,676,732
1,3,0,NA,NA,NA
1,2,0,NA,689,725
1,1,4,1,709,754
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
2,2,0,NA,NA,NA
1,2,0,1,705,734
1,2,0,NA,725,701
2,3,0,1,716,738
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
1,2,0,0,678,528
2,1,3,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,1,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,1,4,1,NA,NA
1,1,1,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,3,1,NA,NA
2,1,4,1,689,734
2,2,0,1,641,694
2,2,0,0,NA,NA
1,3,0,NA,NA,NA
2,2,1,1,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,1,4,NA,666,662
2,3,0,1,NA,NA
2,3,0,1,NA,NA
2,3,3,1,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,714,763
2,3,0,NA,NA,NA
2,3,1,1,NA,NA
2,1,3,NA,NA,NA
2,3,0,NA,NA,NA
1,1,2,1,NA,NA
2,2,0,0,NA,NA
1,1,4,1,731,712
2,2,0,0,NA,NA
1,2,0,1,719,836
1,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,0,0,NA,NA
1,3,0,1,741,763
1,3,0,1,NA,NA
1,3,0,1,647,662
1,3,0,1,758,742
1,1,4,1,705,757
1,3,0,NA,702,715
1,2,0,NA,NA,738
1,1,1,1,NA,NA
1,2,0,NA,689,682
1,1,4,1,655,689
1,3,0,NA,NA,NA
1,2,0,1,727,776
1,1,4,NA,693,716
1,2,1,NA,687,749
1,3,0,NA,696,688
1,3,0,1,NA,NA
2,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,694,665
1,3,3,1,775,706
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,3,1,719,754
1,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,719,836
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,682,745
1,1,2,NA,542,711
1,3,0,0,NA,NA
1,3,0,1,726,727
1,1,2,NA,NA,NA
1,2,0,NA,686,761
1,2,0,1,758,750
1,1,4,0,724,727
1,3,0,1,661,644
1,1,1,NA,NA,NA
1,3,2,1,714,690
1,2,2,NA,719,709
1,2,0,1,715,709
1,2,0,NA,NA,NA
1,1,4,1,679,738
1,3,0,1,729,749
1,1,1,1,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,710,750
1,2,0,NA,NA,NA
1,3,2,1,726,716
1,2,0,1,708,741
1,3,3,1,758,NA
1,3,0,1,769,771
1,3,0,NA,731,NA
1,3,0,1,732,785
1,2,0,NA,NA,NA
1,3,2,NA,744,732
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,708,NA
1,3,0,1,767,NA
1,2,2,1,728,836
1,2,0,1,729,745
1,3,0,1,741,712
1,2,0,NA,NA,NA
1,1,4,1,758,769
1,1,4,1,758,NA
1,2,1,NA,NA,NA
2,3,0,NA,NA,NA
2,1,3,1,NA,NA
1,1,4,1,771,763
1,2,0,NA,NA,NA
3,1,1,1,NA,NA
1,2,0,1,753,740
1,1,4,1,717,778
1,1,2,NA,NA,NA
1,3,0,1,731,727
1,1,4,1,741,836
2,2,3,NA,NA,NA
1,3,0,NA,692,722
1,1,2,1,NA,NA
1,1,4,1,740,763
1,2,0,NA,726,723
1,3,0,NA,NA,NA
1,2,0,NA,727,723
1,1,4,NA,707,836
1,2,0,NA,758,763
1,3,0,0,630,713
1,3,0,1,NA,NA
1,2,0,1,821,776
1,2,0,1,758,720
1,2,0,NA,758,740
1,3,0,1,680,737
1,3,0,0,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,NA,720,722
1,2,0,NA,NA,NA
1,3,0,1,716,740
1,1,4,1,747,760
1,3,0,1,NA,NA
1,1,1,0,NA,NA
1,2,3,NA,697,727
1,1,1,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,0,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
2,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,NA,666,654
1,3,2,1,692,705
1,3,0,1,694,731
1,2,0,NA,NA,NA
1,3,0,NA,707,715
1,3,0,1,674,690
1,2,0,NA,NA,NA
1,1,4,1,733,718
1,1,4,1,743,713
1,1,4,1,487,689
1,1,1,NA,NA,NA
1,1,2,0,NA,NA
2,2,3,1,703,709
1,1,4,1,712,732
1,2,0,1,743,760
1,3,0,1,718,694
1,2,0,NA,714,763
1,3,0,1,695,722
1,2,0,1,727,754
1,2,0,1,714,714
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,1,3,1,722,693
1,2,1,1,NA,NA
1,2,0,1,711,720
1,2,0,NA,758,836
1,1,4,1,758,836
1,1,4,1,731,678
1,2,0,1,821,742
2,2,2,1,711,684
1,2,0,1,821,732
1,1,3,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,3,0,1,706,709
1,1,2,1,NA,NA
1,2,3,1,706,836
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,1,1,1,NA,NA
1,1,4,NA,737,734
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,1,738,836
1,2,1,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
3,3,0,1,821,784
1,1,4,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,682,708
1,3,0,NA,NA,NA
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,3,1,758,794
1,2,0,1,706,757
1,2,0,1,724,741
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,1,2,0,NA,NA
1,2,0,1,758,753
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,679,615
1,3,0,1,763,734
1,3,0,NA,706,700
1,1,4,1,758,750
1,1,4,0,641,677
1,2,0,NA,NA,NA
2,1,3,1,690,699
2,3,3,NA,634,740
1,3,0,1,645,563
2,2,0,1,730,763
1,3,0,NA,NA,NA
1,1,4,1,671,764
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,3,1,NA,NA,NA
1,3,0,1,767,720
1,3,0,NA,NA,NA
1,2,0,NA,744,727
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,731,706
1,2,0,1,738,725
1,3,0,1,666,761
1,2,0,1,713,604
1,1,4,1,708,676
1,1,1,NA,NA,NA
2,2,0,1,NA,NA
1,3,0,NA,688,724
1,1,4,NA,657,701
1,3,0,1,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,712,724
1,1,2,NA,712,736
1,2,0,NA,714,709
1,3,1,NA,667,743
1,1,4,NA,715,721
2,1,2,NA,NA,NA
2,2,0,NA,NA,NA
1,1,4,1,821,702
1,3,0,1,783,702
2,1,2,NA,NA,NA
1,1,4,1,723,724
1,2,0,NA,NA,NA
1,1,3,1,729,704
1,3,0,NA,NA,NA
1,3,0,1,761,750
1,2,1,1,716,725
1,2,1,1,758,761
1,1,1,1,NA,NA
1,1,2,1,NA,NA
1,1,2,1,NA,NA
1,1,4,NA,732,729
1,3,0,NA,731,709
1,2,0,NA,NA,NA
1,1,4,NA,682,679
1,3,0,1,NA,NA
2,2,0,1,675,687
1,3,0,1,721,717
1,1,4,1,698,836
2,1,4,1,758,750
1,3,0,1,693,691
2,1,4,NA,671,706
1,2,0,NA,687,716
1,2,0,NA,709,734
1,1,1,0,NA,NA
1,3,0,1,700,710
1,2,0,NA,NA,NA
1,2,3,0,718,836
1,3,0,NA,NA,NA
1,3,0,1,758,836
1,2,0,1,714,667
1,1,4,1,726,704
1,1,4,1,711,739
1,1,4,1,711,691
1,3,0,1,712,744
1,2,2,1,775,698
1,3,0,NA,727,750
1,1,4,1,675,745
1,1,2,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,691,698
1,1,4,1,758,778
1,1,1,1,NA,NA
1,3,0,NA,NA,695
1,3,0,NA,711,728
2,1,4,0,629,699
1,2,2,NA,740,690
2,2,0,1,NA,NA
2,1,4,NA,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,NA,NA
2,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,NA,741,744
2,3,0,1,NA,NA
2,1,4,NA,NA,NA
2,3,1,1,NA,NA
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,717,702
1,2,0,1,NA,NA
2,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,718,697
2,2,0,NA,NA,NA
2,1,4,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,697,671
1,2,0,1,683,728
1,2,0,1,728,760
1,2,0,1,729,760
1,2,0,NA,579,713
1,3,0,1,683,528
1,3,0,0,695,686
1,3,0,NA,NA,NA
1,3,0,0,NA,NA
1,1,4,1,654,673
1,2,0,1,703,652
1,3,0,1,712,735
1,3,0,1,669,751
2,3,0,1,649,671
1,3,0,NA,821,750
1,2,0,1,740,749
1,3,0,NA,NA,NA
1,3,0,NA,644,597
1,2,0,1,699,710
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,726,737
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,734,836
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,1,4,NA,NA,NA
1,2,0,0,678,650
1,1,4,NA,643,674
1,2,0,1,NA,NA
1,2,3,1,821,696
1,2,0,1,758,724
1,2,0,NA,NA,NA
1,1,4,NA,719,730
1,2,0,1,713,662
2,2,0,1,NA,NA
1,1,1,1,NA,NA
1,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,705,709
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,1,2,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,672,714
1,2,0,0,NA,NA
1,2,0,NA,689,717
1,1,4,NA,697,735
1,2,0,NA,658,763
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,725,738
1,2,0,NA,758,709
1,3,0,1,732,730
1,1,1,1,NA,NA
1,1,1,1,NA,NA
1,3,0,0,NA,NA
2,1,4,1,679,682
1,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,1,741,734
1,2,0,1,728,750
1,1,4,1,758,836
1,3,0,0,717,784
1,1,4,1,707,716
1,3,0,1,703,664
1,3,0,NA,NA,NA
1,1,4,1,697,584
1,2,0,NA,NA,NA
1,2,3,1,691,672
1,1,4,NA,738,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,537,699
1,1,4,1,741,782
1,3,0,NA,758,725
1,3,0,NA,487,725
1,3,0,NA,681,715
1,1,1,1,NA,NA
1,1,4,NA,692,745
1,3,0,1,773,836
1,3,0,NA,NA,NA
1,2,0,0,651,676
1,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,3,0,1,701,711
1,3,0,NA,NA,NA
1,3,0,1,758,760
2,2,0,1,758,673
1,2,1,0,668,689
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,1,NA,744,836
1,2,2,NA,487,742
1,2,0,1,NA,NA
1,3,0,1,692,754
2,2,0,1,NA,NA
1,1,4,NA,740,769
1,3,0,1,740,836
1,2,0,NA,NA,NA
1,1,4,NA,677,731
1,3,0,1,NA,NA
1,1,4,1,711,667
1,2,0,NA,763,761
1,3,0,1,741,735
2,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,0,NA,NA
1,1,3,1,821,703
2,3,0,NA,640,644
1,3,1,NA,741,684
1,1,4,1,665,676
1,1,2,1,NA,NA
1,3,0,0,NA,NA
1,2,0,1,NA,NA
1,2,0,1,730,763
1,3,0,1,769,784
1,1,4,NA,769,711
1,1,4,NA,686,729
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,1,0,NA,NA
1,2,1,NA,758,730
1,2,3,1,769,769
1,1,4,1,702,754
1,2,0,0,NA,NA
1,2,0,1,NA,NA
1,1,4,1,783,758
1,2,0,NA,650,706
1,3,0,1,710,760
1,1,4,1,712,746
1,1,1,1,749,741
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,698,737
1,2,0,NA,727,761
1,2,0,1,709,708
1,1,1,NA,697,756
1,2,0,1,NA,NA
1,3,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,726,716
1,1,4,1,743,702
1,3,0,1,NA,NA
1,1,4,NA,718,763
1,3,0,NA,NA,NA
1,1,4,NA,710,756
1,1,4,NA,NA,NA
1,1,4,1,758,763
1,2,1,NA,NA,NA
1,2,0,NA,680,760
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
6,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,688,743
1,2,0,NA,702,705
1,1,1,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,0,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,727,741
1,1,1,NA,NA,NA
6,1,1,1,NA,NA
2,3,0,1,487,613
2,2,0,0,NA,NA
2,3,2,NA,667,715
2,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,3,NA,NA,NA
1,1,1,0,NA,NA
1,2,1,1,NA,NA
1,2,0,NA,NA,NA
1,1,2,NA,715,768
1,1,1,NA,NA,NA
2,2,0,0,689,646
1,3,0,1,768,713
1,3,0,1,688,694
1,2,0,1,NA,NA
1,3,0,0,NA,NA
2,2,0,NA,NA,NA
1,1,3,NA,NA,NA
1,2,2,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,702,740
1,1,4,1,NA,NA
1,3,0,1,732,700
1,3,0,NA,671,731
1,2,0,1,729,836
1,1,4,1,821,778
1,1,3,0,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,691,836
1,3,1,1,719,715
1,3,0,1,729,701
1,2,0,1,697,756
1,3,0,1,726,738
1,1,4,NA,679,747
1,3,0,1,773,742
1,3,0,NA,734,741
2,3,0,0,664,696
1,2,0,1,NA,NA
1,2,0,1,733,723
1,2,0,0,NA,NA
2,1,2,NA,NA,NA
1,2,1,1,745,760
1,2,0,1,710,716
1,3,0,1,NA,NA
1,3,0,0,702,697
1,1,2,1,NA,NA
1,2,0,1,691,669
2,3,0,NA,702,692
2,1,4,1,821,699
1,1,1,1,701,739
1,1,1,NA,NA,NA
1,2,0,1,678,726
1,3,0,NA,684,739
2,1,4,NA,NA,NA
1,2,0,1,701,624
2,2,0,NA,NA,NA
1,1,4,1,682,666
1,2,0,1,678,745
2,2,0,NA,681,755
1,3,0,1,733,713
1,3,1,1,714,763
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,664,735
1,3,0,1,741,732
1,3,0,1,717,763
1,2,0,1,NA,NA
1,1,4,0,719,647
1,2,0,NA,NA,NA
1,2,3,1,682,661
1,2,0,1,711,684
1,1,1,1,NA,NA
1,1,4,1,758,759
1,2,0,1,NA,NA
1,2,0,0,NA,NA
1,1,1,1,NA,NA
1,3,0,1,821,716
1,3,0,1,709,737
1,1,4,NA,725,693
1,2,0,1,729,528
1,3,0,1,692,726
1,1,4,0,NA,NA
1,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,4,NA,732,699
1,1,4,NA,662,528
1,1,1,1,NA,NA
1,1,4,1,744,701
1,1,4,0,NA,NA
1,1,4,1,702,684
1,1,4,0,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,687,736
2,3,1,NA,NA,NA
2,1,4,NA,690,692
2,1,1,NA,NA,NA
2,3,0,1,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,4,1,740,662
1,3,0,0,NA,NA
1,1,1,1,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,1,1,1,NA,NA
2,3,3,1,NA,NA
2,2,0,1,714,703
2,2,0,NA,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,0,NA,NA
2,1,3,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,1,NA,NA
2,2,0,0,NA,NA
2,3,1,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,1,703,784
1,3,3,1,698,836
1,2,0,1,633,649
1,2,3,1,652,721
1,3,0,NA,NA,NA
1,3,1,1,710,760
1,1,2,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,NA,NA
1,1,4,1,725,784
1,1,4,1,629,621
1,1,4,NA,700,744
1,3,0,1,666,719
1,1,4,NA,702,733
1,3,3,NA,677,672
1,2,0,1,744,751
1,3,0,1,713,677
1,1,2,NA,NA,NA
1,2,0,1,670,682
1,1,3,0,NA,NA
1,3,0,0,NA,NA
1,3,0,NA,727,707
1,2,0,NA,758,750
1,1,3,NA,NA,NA
1,2,0,NA,681,676
1,3,0,NA,678,680
1,3,0,1,715,728
1,1,1,NA,NA,NA
1,1,4,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,711,681
1,3,0,NA,658,675
1,2,0,NA,NA,NA
2,1,4,0,662,621
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
1,3,0,1,743,731
1,3,0,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,701,697
1,1,4,0,741,836
1,3,0,1,NA,NA
1,3,0,1,739,700
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,1,699,713
1,3,0,NA,587,706
1,1,4,NA,638,721
1,3,0,1,NA,NA
1,2,0,1,711,715
1,2,0,NA,NA,NA
1,3,0,1,767,714
1,1,4,1,758,721
1,1,3,1,NA,NA
1,1,4,1,703,760
1,3,0,1,NA,NA
1,2,0,1,NA,NA
1,3,3,1,718,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,3,1,717,695
1,1,1,1,NA,NA
1,3,0,0,NA,NA
1,1,4,1,NA,NA
1,3,0,1,703,738
1,1,4,1,652,NA
1,2,0,1,739,763
1,1,1,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,1,690,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,679,739
1,1,4,1,NA,NA
1,3,0,NA,713,732
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,2,0,0,676,680
2,3,0,NA,NA,NA
2,3,0,NA,693,778
1,2,0,1,707,673
1,2,0,1,728,785
1,2,0,NA,NA,NA
1,2,0,NA,739,781
1,1,4,NA,731,723
1,2,0,1,700,677
1,1,1,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
1,3,2,1,NA,NA
1,1,4,1,738,711
1,3,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,711,778
1,1,1,NA,NA,NA
1,2,1,NA,659,656
1,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,2,3,NA,721,769
1,3,0,1,712,748
1,3,3,1,NA,NA
1,1,1,1,NA,NA
1,2,0,1,712,744
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,2,0,1,765,716
1,2,0,1,736,722
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,2,NA,NA,NA
2,3,0,1,NA,NA
2,2,0,0,NA,NA
1,1,4,1,704,778
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,728,721
1,3,0,1,717,725
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,728,703
1,2,0,NA,721,708
1,3,0,1,738,763
1,2,0,1,711,717
1,2,0,1,697,667
1,2,0,NA,678,728
1,3,0,0,NA,NA
1,1,3,NA,729,700
1,1,4,NA,750,742
1,3,0,0,700,717
1,3,0,1,NA,NA
1,3,3,NA,NA,NA
1,1,1,1,NA,NA
1,1,4,0,679,698
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,758,836
1,1,1,NA,NA,NA
1,1,4,NA,821,753
1,3,0,1,701,717
1,1,4,NA,714,670
1,3,0,NA,723,731
1,3,0,NA,NA,NA
1,3,1,1,686,836
1,3,0,1,741,716
1,3,0,1,NA,NA
1,3,0,NA,687,698
2,1,2,NA,696,662
1,1,4,1,729,763
1,1,4,NA,695,697
1,2,0,1,726,720
1,1,2,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,686,703
1,2,0,1,663,591
1,2,0,1,714,771
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,719,763
1,1,2,NA,NA,NA
1,3,0,1,702,740
1,1,1,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
2,1,2,NA,NA,NA
1,1,3,NA,NA,NA
1,3,0,NA,696,750
1,1,3,NA,NA,NA
1,2,0,1,693,750
1,2,0,1,706,734
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,1,0,NA,NA
1,1,4,1,821,836
1,3,0,NA,710,691
2,2,0,NA,657,710
1,3,0,NA,NA,NA
2,1,4,1,644,628
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,4,1,718,729
1,3,3,1,699,672
2,3,0,NA,NA,NA
1,2,0,1,712,836
1,1,4,0,699,761
1,1,1,NA,NA,NA
1,3,0,1,669,750
1,1,4,1,742,767
1,3,0,NA,626,763
1,2,0,1,NA,NA
1,1,4,1,744,763
1,3,0,NA,677,694
1,1,4,1,710,681
1,1,2,NA,NA,NA
1,3,3,1,730,765
1,3,0,1,NA,NA
1,3,0,1,744,722
1,1,1,1,710,750
1,1,2,NA,NA,NA
1,1,1,NA,NA,NA
1,1,3,NA,NA,NA
1,1,4,1,736,765
1,1,4,1,704,697
1,3,0,1,NA,NA
1,3,0,1,731,781
1,1,3,1,698,723
1,1,2,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,0,NA,NA
1,1,4,1,739,755
1,2,0,1,732,700
1,3,0,1,757,731
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,3,0,NA,653,669
1,2,0,1,758,794
2,3,0,NA,NA,NA
1,1,4,1,708,705
1,3,0,1,739,750
1,1,4,1,731,734
1,2,0,1,821,794
1,2,0,1,723,750
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,1,757,718
1,1,3,1,NA,NA
2,2,1,0,667,686
1,2,0,1,712,782
1,2,1,1,821,764
1,1,1,1,NA,NA
1,3,0,1,711,750
1,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,643,778
1,1,4,NA,718,733
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,725,785
1,3,0,NA,NA,NA
1,2,3,1,741,710
1,3,0,NA,NA,NA
1,1,4,1,726,742
1,3,0,NA,NA,NA
1,1,4,1,702,720
1,2,3,1,712,764
1,3,0,1,650,712
1,1,4,1,720,682
1,3,0,1,732,765
1,3,0,0,NA,NA
1,3,0,1,694,668
1,2,0,1,712,733
1,3,0,1,NA,NA
1,1,4,1,646,528
1,1,4,0,732,734
1,1,4,NA,715,728
1,1,4,1,699,740
1,1,4,1,758,836
1,1,2,NA,NA,NA
1,3,0,1,758,836
2,1,4,NA,743,696
1,2,0,1,719,751
1,3,1,NA,734,NA
2,3,0,NA,NA,NA
1,2,2,1,821,796
2,1,3,NA,NA,NA
2,1,4,1,NA,NA
2,1,4,1,698,723
2,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,768,763
2,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,1,4,1,713,719
2,2,0,NA,NA,NA
2,2,0,0,NA,NA
2,1,4,1,NA,NA
2,1,4,1,NA,NA
2,3,1,0,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,0,707,703
2,1,4,NA,NA,NA
2,2,0,0,NA,NA
2,2,0,1,697,727
2,3,0,1,NA,NA
2,1,2,NA,NA,NA
1,3,0,1,NA,NA
1,3,3,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,1,684,735
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,1,3,NA,NA,NA
1,1,4,NA,769,750
2,3,0,NA,NA,NA
2,3,2,NA,NA,NA
2,3,1,NA,684,725
2,3,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,1,NA,NA
2,2,0,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,1,719,745
1,2,0,1,712,784
1,3,0,1,647,719
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,1,1,NA,NA
1,2,0,1,716,761
1,2,0,1,758,755
1,3,0,1,706,708
1,2,0,NA,758,747
1,2,0,NA,NA,NA
1,3,2,1,702,745
1,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,1,707,706
1,2,0,1,NA,NA
1,1,4,NA,736,782
1,1,1,1,NA,NA
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,715,692
6,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,637,722
1,3,0,NA,675,559
1,2,0,1,NA,NA
2,3,0,1,722,698
1,3,0,0,671,714
1,1,3,0,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,741,742
1,2,1,NA,664,686
1,1,1,1,NA,NA
1,3,0,1,NA,NA
1,2,0,1,NA,NA
1,1,2,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,758,771
1,2,0,1,NA,NA
1,3,0,1,734,745
1,2,0,1,NA,NA
1,1,4,NA,728,760
1,1,1,NA,NA,NA
1,1,4,1,711,710
1,2,0,1,758,716
1,1,2,1,NA,NA
1,3,0,1,758,702
1,1,1,NA,NA,NA
1,3,0,1,682,707
1,2,0,0,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,1,0,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,3,1,716,745
1,1,4,1,747,NA
1,1,3,1,NA,NA
1,1,4,1,NA,NA
1,1,4,1,NA,NA
1,2,0,1,668,741
1,3,0,1,695,700
1,3,0,NA,697,725
1,1,4,1,673,690
1,3,0,0,697,645
1,3,0,1,717,735
1,3,0,NA,NA,NA
1,1,4,1,703,729
1,3,0,NA,758,711
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,678,738
1,2,0,NA,732,740
1,2,3,1,758,724
1,1,3,NA,NA,NA
1,2,0,NA,691,836
1,2,0,NA,NA,NA
1,3,0,NA,724,763
1,3,0,NA,742,721
1,2,0,NA,NA,NA
1,3,2,NA,712,836
2,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,1,707,728
1,2,3,1,758,760
1,3,0,NA,678,710
1,2,3,1,NA,NA
1,1,4,NA,684,784
1,1,1,0,NA,NA
1,2,0,1,NA,NA
1,3,0,1,706,698
1,1,4,NA,718,734
1,1,4,NA,714,748
1,1,4,NA,752,771
1,2,0,NA,NA,NA
1,3,0,NA,698,677
1,3,1,1,NA,NA
1,2,0,NA,675,714
1,2,0,1,654,700
1,1,1,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,666,836
1,3,0,NA,710,712
1,2,0,1,722,728
1,2,0,1,628,604
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,0,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,740,761
1,1,2,1,NA,NA
1,2,0,NA,715,738
1,3,0,0,675,693
1,2,0,0,NA,NA
1,2,0,1,723,794
1,3,0,1,682,771
2,3,0,1,758,740
1,3,0,1,NA,NA
1,1,4,1,703,735
2,3,0,NA,669,705
1,1,1,NA,NA,NA
1,1,1,1,NA,NA
1,2,0,0,NA,NA
1,3,0,1,655,686
1,1,1,1,703,714
1,2,0,0,NA,NA
1,2,0,0,NA,NA
1,1,3,NA,NA,NA
1,3,0,1,738,760
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,1,658,689
2,2,3,1,NA,NA
1,2,0,NA,NA,NA
1,1,4,NA,NA,NA
1,3,0,1,NA,673
2,3,0,1,NA,NA
1,1,4,NA,665,721
1,1,1,NA,NA,NA
1,1,3,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,670,684
1,1,3,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,727,703
2,1,4,1,NA,NA
1,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,0,NA,NA
1,2,0,1,647,710
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,719,741
1,2,0,1,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,3,NA,659,626
1,3,0,1,624,686
1,2,0,0,688,719
2,3,0,NA,487,642
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,0,NA,NA
1,2,0,1,693,692
1,2,0,1,708,731
1,2,0,NA,NA,NA
1,3,0,1,683,725
1,1,4,NA,718,836
1,2,0,1,693,725
1,1,4,1,689,713
1,1,4,NA,757,726
1,1,4,1,704,700
1,1,4,1,758,717
1,2,0,NA,NA,NA
1,2,1,1,675,720
1,1,4,NA,662,724
1,2,0,1,749,738
1,1,4,1,694,684
1,3,0,1,690,734
1,3,0,NA,710,729
1,3,0,NA,NA,NA
1,1,4,1,686,698
1,1,1,NA,NA,NA
1,2,0,1,767,699
2,1,2,0,NA,NA
1,2,0,1,744,734
1,2,2,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,696,703
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,700,794
1,2,0,NA,NA,NA
1,2,0,NA,648,683
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,1,4,1,728,782
1,1,1,1,714,784
2,1,4,1,689,693
2,2,0,NA,NA,NA
1,3,0,1,821,719
2,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,1,4,1,717,770
1,2,0,NA,672,554
1,2,0,NA,NA,NA
1,2,1,1,696,707
1,2,0,NA,758,741
1,2,0,1,758,739
1,2,0,1,NA,NA
1,1,4,1,663,706
1,2,0,1,725,711
1,1,4,1,773,836
1,2,0,NA,NA,NA
1,1,4,1,701,752
1,2,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,725,760
1,1,4,1,692,760
1,2,3,1,715,746
1,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,695,722
1,2,0,NA,702,731
1,1,4,1,727,782
1,3,0,1,732,699
1,3,0,1,717,794
1,3,0,1,NA,NA
1,3,0,0,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,555,658
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,1,707,718
2,1,4,NA,657,677
1,3,0,1,647,695
1,2,0,1,724,709
2,1,4,NA,NA,NA
1,3,0,1,649,750
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,2,1,785,760
1,2,0,1,739,836
1,1,4,1,738,785
2,1,1,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,1,0,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,2,1,707,669
2,2,0,1,NA,NA
2,1,3,1,684,674
2,1,2,NA,NA,NA
1,1,3,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,NA,NA,NA
1,2,0,0,NA,NA
2,3,0,1,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,1,739,741
2,3,0,NA,NA,NA
2,2,0,1,NA,NA
2,3,1,1,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,4,NA,711,663
2,2,0,1,727,750
2,3,0,0,NA,NA
2,1,1,1,NA,NA
1,2,0,1,NA,NA
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,1,NA,NA
2,1,4,1,NA,NA
2,3,0,1,660,677
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,3,NA,NA,NA
2,1,4,NA,NA,NA
2,2,0,1,NA,NA
2,1,4,NA,643,660
2,1,1,0,NA,NA
2,1,1,1,NA,NA
1,2,0,1,699,751
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,680,684
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,688,680
1,2,0,1,682,695
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
1,2,1,1,684,755
1,2,0,0,NA,NA
1,1,4,1,715,696
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,696,712
1,1,4,NA,684,745
1,2,0,NA,NA,NA
1,2,0,1,724,690
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,1,741,745
1,3,0,NA,NA,NA
1,2,0,1,705,652
1,3,0,1,653,700
1,1,4,1,697,731
1,2,2,1,725,763
1,3,3,1,726,781
1,1,1,NA,NA,NA
1,1,4,1,739,692
1,1,4,1,650,667
1,2,3,1,740,836
2,3,0,1,716,724
1,3,0,NA,694,752
1,1,4,1,758,782
1,3,0,1,630,706
1,3,0,1,705,750
1,3,0,1,NA,NA
2,3,0,NA,NA,NA
1,2,0,0,695,741
2,2,3,1,664,717
2,2,0,NA,NA,NA
1,2,0,NA,739,743
1,3,0,1,708,738
1,2,3,1,685,711
1,2,0,1,707,731
1,2,0,NA,NA,NA
1,2,0,NA,724,836
1,3,0,1,690,721
1,1,1,1,688,698
1,3,2,NA,725,760
1,2,0,1,716,682
1,2,0,1,NA,NA
1,3,0,1,652,680
1,2,2,NA,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,4,NA,725,740
1,3,0,0,641,695
1,1,2,1,NA,NA
1,1,1,1,NA,NA
1,3,0,0,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,723,753
2,3,0,1,671,690
1,2,0,1,744,736
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,723,NA
1,2,0,NA,NA,NA
1,2,0,1,707,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,1,1,NA,NA
1,1,1,0,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,1,1,1,NA,NA
2,3,0,NA,NA,NA
1,1,4,NA,663,663
1,3,0,1,701,836
1,2,0,1,NA,NA
1,1,4,1,736,726
1,2,0,NA,765,750
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,2,2,1,758,836
1,2,0,1,NA,NA
1,2,0,1,678,745
1,1,4,1,669,655
1,3,0,1,NA,NA
2,1,3,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,653,708
1,2,0,NA,706,693
1,2,0,1,684,674
1,1,4,1,718,712
1,1,4,1,706,748
1,3,1,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,702,705
1,3,0,1,693,729
1,2,0,1,764,760
1,2,0,1,685,688
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,3,0,1,NA,NA
1,1,2,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,695,734
1,1,4,NA,688,639
1,3,0,NA,699,711
1,1,4,NA,626,662
1,1,1,NA,NA,NA
1,1,1,1,659,682
1,1,3,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,1,NA,NA,NA
1,3,0,0,705,740
1,2,0,NA,NA,NA
1,2,0,1,720,836
2,2,0,0,739,725
1,2,0,NA,722,687
1,3,0,1,758,732
1,1,3,NA,NA,NA
1,3,0,NA,716,761
1,3,0,NA,NA,NA
1,3,0,NA,704,697
1,1,4,1,633,746
1,1,1,NA,NA,NA
1,2,0,1,724,745
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,715,784
1,3,0,1,NA,NA
1,3,3,1,710,763
1,3,0,NA,689,722
2,1,4,NA,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,0,668,691
1,2,0,1,NA,NA
2,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,3,2,1,NA,NA
2,3,2,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,664,726
1,3,1,NA,NA,NA
1,2,0,1,NA,NA
1,1,3,1,NA,NA
1,3,0,1,NA,NA
1,2,0,1,683,679
1,1,4,NA,741,742
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,694,654
1,2,0,1,672,709
1,2,0,NA,NA,NA
1,1,4,1,726,676
1,3,0,1,702,674
2,1,4,0,709,713
1,2,0,NA,NA,NA
1,1,4,NA,689,836
1,1,2,NA,NA,NA
1,2,0,NA,696,725
1,2,0,1,724,794
1,3,1,NA,NA,NA
1,3,0,NA,765,836
1,2,0,1,741,836
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,2,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,NA,712,733
1,2,0,1,721,701
1,3,0,1,NA,NA
1,1,2,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,735,724
1,2,0,NA,690,724
1,3,0,1,NA,NA
1,2,0,1,702,681
1,2,1,1,705,731
1,3,0,1,740,657
1,3,0,1,769,736
2,3,0,1,NA,NA
1,1,4,1,698,778
1,1,3,NA,NA,NA
1,2,0,1,701,720
1,3,0,1,NA,NA
1,2,0,1,714,704
2,2,3,NA,740,528
1,3,1,1,715,715
1,2,0,1,741,694
1,2,0,NA,NA,NA
1,2,3,NA,744,750
1,1,3,0,NA,NA
2,2,3,1,707,676
1,1,4,1,743,767
2,1,2,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,758,721
1,3,0,1,688,737
1,2,0,1,686,736
1,1,3,1,NA,NA
2,1,3,0,NA,NA
1,1,4,1,767,785
1,2,0,1,NA,NA
1,2,0,1,678,703
1,3,0,1,740,714
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,701,726
1,2,0,0,NA,NA
2,2,1,NA,NA,NA
2,2,0,0,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,2,1,1,NA,NA
2,3,2,1,NA,NA
2,3,0,1,NA,NA
1,1,4,1,702,721
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
1,1,4,NA,683,617
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,1,1,741,728
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,4,1,NA,NA
2,2,0,NA,NA,NA
1,3,0,0,NA,NA
2,3,1,NA,NA,NA
2,1,2,1,NA,NA
2,1,1,NA,NA,NA
2,2,0,1,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
2,3,0,0,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,1,4,1,740,731
1,2,0,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,696,668
2,3,0,1,741,679
2,3,0,NA,NA,NA
2,3,0,NA,625,528
2,1,3,0,NA,NA
2,1,4,0,694,706
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,1,NA,NA
2,3,3,NA,704,697
2,1,1,1,NA,NA
2,3,2,NA,NA,NA
1,2,1,1,707,785
1,1,4,1,717,716
1,3,0,NA,NA,NA
1,2,0,1,701,778
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,2,2,NA,NA,NA
1,2,0,1,720,741
1,3,0,1,758,794
1,2,0,NA,653,617
2,3,0,NA,NA,NA
1,2,0,NA,726,738
1,3,0,0,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,715,728
1,1,1,1,NA,NA
1,2,0,NA,NA,NA
1,3,1,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,696,649
1,3,0,NA,NA,NA
1,3,0,1,671,702
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,1,707,724
1,3,0,1,744,731
1,3,0,1,NA,NA
1,2,0,1,721,738
1,3,0,1,703,635
1,2,0,0,582,560
1,3,0,0,608,673
1,1,2,NA,NA,NA
1,1,4,NA,529,667
1,2,0,NA,NA,NA
1,2,0,0,716,680
1,1,1,0,NA,NA
1,2,0,0,722,700
1,1,2,1,728,712
1,1,4,1,718,836
1,2,0,NA,NA,NA
1,3,1,NA,NA,NA
1,2,0,NA,691,697
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,683,705
1,3,2,1,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,NA,NA
1,2,0,0,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,2,1,NA,NA
1,2,3,0,688,739
1,2,3,1,704,681
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,2,1,698,741
1,3,1,1,679,715
2,1,4,NA,674,667
2,1,3,NA,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,670,707
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,NA,NA
2,1,3,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,1,NA,NA
2,1,1,NA,NA,NA
2,1,4,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,3,1,667,622
2,3,0,1,NA,NA
1,1,4,1,648,700
1,2,0,NA,NA,NA
1,3,3,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,672,690
1,3,0,0,703,734
1,3,0,1,700,735
1,1,4,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,NA,718,782
1,1,2,NA,NA,NA
2,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,670,683
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1,2,0,1,747,778
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1,1,1,1,715,718
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1,2,2,NA,710,740
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2,3,0,NA,NA,NA
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1,1,4,1,771,756
2,1,1,0,NA,NA
1,1,4,NA,675,708
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6,1,4,NA,758,836
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1,1,4,1,646,741
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1,2,0,1,NA,NA
1,1,3,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,676,682
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,1,3,1,NA,NA
1,2,3,NA,715,758
1,2,0,NA,714,649
2,2,0,1,695,742
1,1,4,1,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,1,NA,NA,NA
2,1,3,0,NA,NA
1,1,1,1,765,758
1,1,1,NA,NA,NA
2,2,0,NA,NA,NA
1,2,2,1,700,716
1,2,0,NA,643,666
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,3,1,NA,NA,NA
1,1,3,1,NA,NA
1,1,1,NA,NA,NA
1,1,4,NA,724,712
2,1,1,NA,NA,NA
2,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,1,NA,NA,NA
1,3,0,0,758,667
1,1,4,1,647,731
1,3,0,NA,NA,NA
4,1,4,NA,744,760
1,2,0,1,NA,NA
3,1,3,NA,NA,NA
2,1,4,NA,696,763
1,2,0,NA,NA,NA
1,2,0,NA,710,756
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,1,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,693,736
1,3,0,1,712,717
1,1,4,1,727,755
1,2,0,1,695,702
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,689,670
1,3,0,NA,NA,NA
1,1,4,1,714,734
1,2,0,1,NA,NA
1,1,4,NA,568,657
1,1,4,1,765,771
6,1,3,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,724,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,1,726,639
4,3,0,NA,NA,NA
1,2,0,NA,639,680
1,1,3,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,1,739,715
1,1,1,NA,NA,NA
1,2,0,1,704,702
1,1,1,1,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,705,718
3,1,4,1,698,703
1,2,0,NA,NA,NA
1,2,3,1,688,660
1,2,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,4,NA,NA,NA
1,1,2,1,NA,NA
1,1,4,NA,649,NA
1,1,2,NA,NA,NA
1,1,4,1,NA,NA
1,1,4,1,NA,NA
1,1,2,0,NA,NA
1,1,1,NA,NA,NA
1,1,4,0,NA,NA
1,1,3,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,3,3,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,694,691
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,0,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
1,1,2,NA,NA,NA
1,2,0,1,693,740
1,3,0,1,NA,NA
1,1,1,NA,NA,NA
4,1,1,NA,NA,NA
6,1,1,NA,NA,NA
2,1,2,0,NA,NA
2,1,1,0,NA,NA
2,1,4,1,692,711
3,2,0,0,694,744
1,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,NA,NA
1,2,0,1,758,699
1,2,0,1,695,715
1,2,0,1,731,711
1,2,0,1,665,729
1,1,1,NA,NA,NA
2,1,4,NA,696,703
1,1,4,1,740,580
1,3,0,1,758,742
1,3,0,NA,NA,NA
1,3,0,1,721,731
1,3,0,1,726,713
1,3,0,1,758,778
1,3,0,0,NA,NA
1,1,3,NA,694,718
2,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,1,711,701
2,2,1,NA,NA,NA
2,2,0,1,NA,NA
2,2,0,1,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,2,2,1,NA,NA
1,3,0,1,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
2,2,3,NA,691,643
2,2,0,NA,620,528
2,2,0,0,NA,NA
2,2,0,NA,NA,NA
2,1,1,1,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,1,NA,NA
1,1,1,NA,NA,NA
2,1,3,1,NA,NA
1,2,0,1,696,778
1,2,0,1,702,726
1,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,1,3,NA,683,676
1,3,3,NA,699,702
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,2,1,NA,NA,NA
1,3,0,NA,712,796
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,3,NA,NA,NA
1,2,0,1,725,729
1,2,2,1,724,761
1,1,1,NA,NA,NA
1,1,2,NA,NA,NA
1,3,1,NA,NA,NA
2,2,0,0,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
2,3,0,NA,NA,NA
2,1,2,NA,NA,NA
2,3,0,NA,NA,NA
2,1,1,0,NA,NA
2,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,3,0,1,702,720
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,747,675
1,3,0,1,660,713
1,3,0,NA,NA,NA
1,1,3,NA,NA,NA
1,3,0,1,NA,NA
1,2,0,1,NA,NA
1,3,0,NA,NA,NA
4,1,4,NA,735,715
1,1,4,NA,719,706
1,3,0,NA,707,748
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,2,0,0,NA,NA
1,2,0,1,NA,NA
1,2,0,NA,694,778
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,1,3,NA,NA,NA
1,1,4,NA,700,771
1,2,0,NA,NA,NA
6,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,2,1,NA,NA,NA
2,3,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,1,700,836
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
1,1,1,NA,NA,NA
1,1,3,1,NA,NA
1,3,0,NA,821,768
1,2,1,0,NA,NA
1,1,2,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,758,763
1,3,0,1,704,718
1,1,4,1,NA,710
1,1,2,NA,NA,NA
1,3,0,1,714,750
1,3,0,NA,NA,NA
1,3,0,1,659,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,3,0,1,719,741
1,3,0,1,640,732
3,2,0,NA,NA,NA
1,1,4,1,758,720
1,3,0,NA,NA,NA
1,3,0,1,653,665
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
1,3,0,1,573,528
1,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,1,4,1,710,732
1,1,4,1,639,750
1,1,1,NA,NA,NA
1,2,1,1,717,711
1,2,0,NA,NA,721
2,3,0,1,NA,NA
1,1,2,NA,NA,NA
1,1,1,1,NA,NA
1,2,0,NA,767,745
1,2,0,NA,NA,NA
1,1,2,1,714,725
1,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,3,0,NA,NA,NA
1,1,2,NA,NA,NA
1,1,1,0,NA,NA
1,3,0,NA,NA,NA
2,2,0,NA,NA,NA
1,1,4,1,699,694
2,3,0,NA,NA,NA
1,2,2,NA,NA,NA
2,2,0,NA,NA,NA
1,1,1,NA,NA,NA
1,3,0,1,676,731
1,3,0,NA,NA,NA
1,2,0,1,NA,NA
1,1,4,1,704,685
1,2,1,NA,738,724
1,2,0,NA,NA,NA
1,3,0,0,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,710,732
1,3,0,1,NA,NA
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
2,3,0,NA,739,750
1,3,0,NA,696,727
1,3,0,1,NA,NA
1,2,0,NA,NA,NA
1,2,2,0,719,750
1,1,1,NA,NA,NA
1,3,0,NA,NA,NA
3,2,0,NA,NA,NA
1,2,0,NA,NA,NA
1,3,0,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,1,NA,NA
1,1,2,1,NA,NA
1,3,0,NA,NA,NA
1,3,0,NA,NA,NA
1,1,4,NA,NA,NA
1,3,0,1,727,667
1,3,0,NA,NA,NA
1,1,1,1,647,669
1,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,1,1,NA,NA,NA
2,3,0,NA,NA,NA
1,3,0,0,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
NA,1,1,NA,NA,NA
2,2,0,NA,NA,NA
2,3,1,NA,NA,NA
1,2,0,1,NA,NA
NA,2,0,NA,NA,NA
2,2,0,NA,NA,NA
2,1,1,NA,NA,NA
NA,2,0,NA,NA,NA
2,2,0,NA,NA,NA
1,2,0,NA,NA,NA
2,2,0,0,NA,NA
1,1,1,NA,NA,NA
1,1,1,NA,NA,NA
================================================
FILE: CAUSALITY/causality-tidy.R
================================================
## ---- message=FALSE---------------------------------------
## Load required packages
library(tidyverse)
library(qss)
## Load in the data from QSS package
data(resume, package = "qss")
## ---------------------------------------------------------
## Or read in a saved CSV
resume <- read_csv("CAUSALITY/resume.csv")
## ---- message=FALSE---------------------------------------
resume <- read_csv("CAUSALITY/resume.csv",
col_types = cols(
firstname = col_character(),
sex = col_character(),
race = col_character(),
call = col_number()))
## ---------------------------------------------------------
dim(resume)
## ---------------------------------------------------------
head(resume)
tail(resume)
glimpse(resume)
## ---------------------------------------------------------
summary(resume)
## ---- message=FALSE---------------------------------------
race.call.summary <- resume %>%
group_by(race, call) %>% # create for each race and callback status
count()
race.call.summary
## ---- message=FALSE---------------------------------------
race.call.tab <- race.call.summary %>%
pivot_wider(names_from = call, # reshape the data
values_from = n)
race.call.tab
## ---------------------------------------------------------
race.call.tab.names <- race.call.tab %>%
rename(no_callback = "0",
callback = "1")
race.call.tab.names
## ---------------------------------------------------------
race.call.tab.names <- race.call.tab.names %>%
mutate(total_resumes = no_callback + callback,
callback_prop = callback / total_resumes)
race.call.tab.names
## ---------------------------------------------------------
overall_callback <- resume %>%
summarize(total_callback_rate = sum(call) / n())
overall_callback
## ---------------------------------------------------------
overall_callback <- resume %>%
summarize(total_callback_rate = mean(call))
overall_callback
## ---- message=FALSE---------------------------------------
callback_by_race <- resume %>%
group_by(race) %>%
summarize(callback_rate = mean(call))
callback_by_race
## ---------------------------------------------------------
class(TRUE)
## ---------------------------------------------------------
as.integer(TRUE)
as.integer(FALSE)
## ---------------------------------------------------------
x <- c(TRUE, FALSE, TRUE) # a vector with logical values
mean(x) # proportion of TRUEs
sum(x) # number of TRUEs
## ---------------------------------------------------------
FALSE & TRUE
TRUE & TRUE
## ---------------------------------------------------------
TRUE | FALSE
FALSE | FALSE
## ---------------------------------------------------------
TRUE & FALSE & TRUE
## ---------------------------------------------------------
(TRUE | FALSE) & FALSE # the parentheses evaluate to TRUE
TRUE | (FALSE & FALSE) # the parentheses evaluate to FALSE
## ---------------------------------------------------------
TF1 <- c(TRUE, FALSE, FALSE)
TF2 <- c(TRUE, FALSE, TRUE)
TF1 | TF2
TF1 & TF2
## ---------------------------------------------------------
4 > 3
"Hello" == "hello" # R is case-sensitive
"Hello" != "hello"
## ---------------------------------------------------------
x <- c(3, 2, 1, -2, -1)
x >= 2
x != 1
## ---------------------------------------------------------
## logical conjunction of two vectors with logical values
(x > 0) & (x <= 2)
## logical disjunction of two vectors with logical values
(x > 2) | (x <= -1)
## ---------------------------------------------------------
x.int <- (x > 0) & (x <= 2) # logical vector
x.int
mean(x.int) # proportion of TRUEs
sum(x.int) # number of TRUEs
## ---------------------------------------------------------
## callback rate for black-sounding names
resume %>%
filter(race == "black") %>% # only keep observations where "race" is black
summarize(mean(call)) # take the average of call
## ---------------------------------------------------------
## Subset the data with black names
resumeB <- filter(resume, race == "black")
## Calculate the mean callback rate
summarize(resumeB, mean(call))
## with $ operator to run mean() on the call column
mean(resumeB$call)
## ---------------------------------------------------------
resumeBf <- filter(resume, race == "black" & sex == "female")
## ---------------------------------------------------------
## callback rate for black female names
Bf_callback <- filter(resume, race == "black" & sex == "female") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Bf_callback)
## callback rate for black male names
Bm_callback <- filter(resume, race == "black" & sex == "male") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Bm_callback)
## callback rate for white female names
Wf_callback <- filter(resume, race == "white" & sex == "female") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Wf_callback)
## callback rate for white male names
Wm_callback <- filter(resume, race == "white" & sex == "male") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Wm_callback)
## difference between white women and black women
Wf_callback - Bf_callback
## difference between white men and black men
Wm_callback - Bm_callback
## ---- message=FALSE---------------------------------------
racial_gaps_by_sex <- resume %>%
group_by(race, sex) %>% # using two variables to group the data
summarize(callback = mean(call)) %>% # the callback rate for each group
pivot_wider(names_from = race, # reshaping the data
values_from = callback) %>%
mutate(race_gap = white - black)
print(racial_gaps_by_sex)
## ---- message=FALSE---------------------------------------
## what happens in this portion of the code?
resume %>%
group_by(race, sex) %>%
summarize(callback = mean(call))
## What happens after we add the pivot_wider()?
resume %>%
group_by(race, sex) %>%
summarize(callback = mean(call)) %>%
pivot_wider(names_from = race,
values_from = callback)
## And so on
## ---------------------------------------------------------
resume <- resume %>%
## create a new variable that is 1 if the resume is black and female,
## 0 otherwise
mutate(BlackFemale = if_else(race == "black" &
sex == "female", 1, 0))
## ---------------------------------------------------------
# Rows in the resumeBf data
nrow(resumeBf)
# Is that equal to sum of BlackFemale?
nrow(resumeBf) == resume %>% summarize(bf = sum(BlackFemale))
## ---------------------------------------------------------
resume_fact <- resume %>%
mutate(type = if_else(race == "black" & sex == "female", "BlackFemale", ""),
type = if_else(race == "black" & sex == "male", "BlackMale", type),
type = if_else(race == "white" & sex == "female", "WhiteFemale", type),
type = if_else(race == "white" & sex == "male", "WhiteMemale", type))
head(resume_fact)
## ---------------------------------------------------------
resume <- resume %>%
## add a categorical variable for race/gender type
mutate(type = case_when(race == "black" & sex == "female" ~ "BlackFemale",
race == "white" & sex == "female" ~ "WhiteFemale",
race == "black" & sex == "male" ~ "BlackMale",
race == "white" & sex == "male" ~ "WhiteMale",
TRUE ~ "other"
))
head(resume)
## Did any observations receive the "other" value for type?
filter(resume, type == "other")
## ---------------------------------------------------------
## check object class
class(resume$type)
## coerce the character variable into a factor variable
resume <- resume %>%
mutate(type = as.factor(type))
## look at the levels of the factor
levels(resume$type)
## ---- message=FALSE---------------------------------------
firstname_callback <- resume %>%
group_by(firstname) %>%
select(firstname, call) %>%
summarize(callback = mean(call))
head(firstname_callback)
## ---------------------------------------------------------
slice(resume, 1)
## ---- label='naming-shaming', echo = FALSE, out.width='75%', fig.align = 'center', fig.cap= '(ref:name-shame-cap)', fig.scap="Naming-and-shaming get-out-the-vote message"----
knitr::include_graphics("CAUSALITY/naming-shaming.pdf")
## ---------------------------------------------------------
## Load in the data from QSS package
data(resume, package = "qss")
## Or from a csv
social <- read_csv("CAUSALITY/social.csv",
col_types = cols(sex = col_character(),
yearofbirth = col_double(),
primary2004 = col_double(),
messages = col_character(),
primary2006 = col_double(),
hhsize = col_double()))
summary(social) # summarize the data
## ---- message=FALSE---------------------------------------
## Average turnout by treatment message
turnout_by_message <- social %>%
group_by(messages) %>%
summarize(turnout = mean(primary2006))
turnout_by_message
## Differences between treatment(s) and control means
turnout_diffs <- turnout_by_message %>%
pivot_wider(names_from = messages,
values_from = turnout) %>%
mutate(diff_Civic_Duty = `Civic Duty` - Control,
diff_Hawthorne = Hawthorne - Control,
diff_Neighbors = Neighbors - Control) %>%
select(diff_Civic_Duty, diff_Hawthorne, diff_Neighbors)
turnout_diffs
## ---- message=FALSE---------------------------------------
social %>%
mutate(age = 2006 - yearofbirth) %>%
group_by(messages) %>%
summarize(age_avg = mean(age),
primary2004_avg = mean(primary2004),
hhsize_avg = mean(hhsize))
## ---- message=FALSE---------------------------------------
minwage <- read_csv("CAUSALITY/minwage.csv") # load the data
## or
data(minwage, package = "qss")
dim(minwage) # dimension of data
glimpse(minwage)
summary(minwage) # summary of data
## ---- message=FALSE---------------------------------------
## Add a 'state' variable
minwage <- minwage %>%
mutate(state = if_else(location == "PA", "PA", "NJ"))
## Create the 'new_wage' object
new_wage <- 5.05
## Calculate the proportions above and below the new wage by state
state_props <- minwage %>%
mutate(above_min_before = if_else(wageBefore >= new_wage, 1, 0),
above_min_after = if_else(wageAfter >= new_wage, 1, 0)) %>%
group_by(state) %>%
summarize(prop_before = mean(above_min_before),
prop_after = mean(above_min_after))
state_props
## ---- message=FALSE---------------------------------------
## First create new variables to calculate the
## proportion of full-time employees
minwage <- minwage %>%
mutate(totalAfter = fullAfter + partAfter,
fullPropAfter = fullAfter / totalAfter)
## Then calculate the average proportion of full-time workers by state
full_prop_by_state <- minwage %>%
group_by(state) %>%
summarize(fullPropAfter = mean(fullPropAfter))
## To calculate the difference between states, we use pivot_wider()
## and mutate()
pivot_wider(full_prop_by_state,
names_from = state, values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
## ---- message = FALSE-------------------------------------
chains_by_state <- minwage %>%
group_by(state) %>%
count(chain) %>%
mutate(prop = n / sum(n)) %>%
pivot_wider(-n, # this drops the 'n' variable prior to pivoting
names_from = state,
values_from = prop)
chains_by_state
## ----message=FALSE, warning=FALSE-------------------------
full_prop_by_state_chain <- minwage %>%
group_by(state, chain) %>%
summarize(fullPropAfter = mean(fullPropAfter)) %>%
pivot_wider(names_from = state,
values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
full_prop_by_state_chain
## ---- message = FALSE-------------------------------------
prop_by_state_chain_location_subset <- minwage %>%
filter(!location %in% c("shoreNJ", "centralNJ")) %>%
group_by(state, chain) %>%
summarize(fullPropAfter = mean(fullPropAfter)) %>%
pivot_wider(names_from = state,
values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
prop_by_state_chain_location_subset
## ---------------------------------------------------------
## First, create a variable for the full-time
## proportion prior to the change
minwage <- minwage %>%
mutate(totalBefore = fullBefore + partBefore,
fullPropBefore = fullBefore / totalBefore)
## Then look at the differences in average proportion of full-time
## before and after (in NJ only)
minwage %>%
filter(state == "NJ") %>%
summarize(diff = mean(fullPropAfter) - mean(fullPropBefore))
## ----DiD-plot, dev='pdf', fig.show='hide', echo=FALSE-----
minwagePA <- filter(minwage, state == "PA")
minwageNJ <- filter(minwage, state == "NJ")
x <- seq(from = 0.2, to = 0.8, length = 10)
#y0 <- seq(from = 0.1, to = 0.4, length = 10)
y0 <- seq(from = mean(minwagePA$fullPropBefore),
to = mean(minwagePA$fullPropAfter), length = 10)
#y1 <- seq(from = 0.3, to = 0.8, length = 10)
y1 <- seq(from = mean(minwageNJ$fullPropBefore),
to = mean(minwageNJ$fullPropAfter), length = 10)
est <- mean(minwageNJ$fullPropBefore) -
mean(minwagePA$fullPropBefore)
baseplot <- function() {
plot(x, y0, type = "l", xlim = c(0, 1.2), ylim = c(0.24, 0.36), col = "red", lwd = 1.5,
xlab = "", ylab = "Average proportion of full-time employees", xaxt = "n")
points(x[c(1, 10)], y0[c(1, 10)], pch = 1, col = "red")
lines(x, y1, lwd = 1.5, col = "black")
points(x[1], y1[1], pch = 19, col = "black")
points(x[10], y1[10], pch = 19, col = "black")
text(lab = "treatment group\n (New Jersey)", 0.8, 0.335, col = "black")
text(lab = "control group\n (Pennsylvania)", 0.2, 0.3225, col = "red")
mtext("Before", side = 1, at = 0.2, line = 1)
mtext("After", side = 1, at = 0.8, line = 1)
}
## DiD
baseplot()
lines(x, y0+est, lwd = 1.5, lty = "dashed", col = "black")
points(x[10], y0[10]+est, pch = 17, col = "black")
text(lab = "counterfactual\n (New Jersey)", 0.8, 0.2475, col = "black")
# function to draw curly braces
# x, y position where to put the braces
# range is the length of the brace
# position: 1 vertical, 2 horizontal
# direction: 1 left/down, 2 right/up
# depth controls width of the shape
CurlyBraces <- function(x0, x1, y0, y1, pos = 1, direction = 1, depth = 1, color = "black") {
a=c(1,2,3,48,50) # set flexion point for spline
b=c(0,.2,.28,.7,.8) # set depth for spline flexion point
curve = spline(a, b, n = 50, method = "natural")$y * depth
curve = c(curve,rev(curve))
if (pos == 1){
a_sequence = seq(x0,x1,length=100)
b_sequence = seq(y0,y1,length=100)
}
if (pos == 2){
b_sequence = seq(x0,x1,length=100)
a_sequence = seq(y0,y1,length=100)
}
# direction
if(direction==1)
a_sequence = a_sequence+curve
if(direction==2)
a_sequence = a_sequence-curve
# pos
if(pos==1)
lines(a_sequence,b_sequence, lwd=1.5, xpd=NA, col = color) # vertical
if(pos==2)
lines(b_sequence,a_sequence, lwd=1.5, xpd=NA, col = color) # horizontal
}
CurlyBraces(x0=0.82, x1=0.82, y0=y0[10]+est, y1=y1[10], pos = 1, direction = 1,
depth=0.05, color = "blue")
text(1.05, 0.29, "average\n causal effect\n estimate")
## ---- message=FALSE---------------------------------------
## DiD estimate
minwage %>%
group_by(state) %>%
## difference before and after
summarize(diff = mean(fullPropAfter) - mean(fullPropBefore)) %>%
pivot_wider(names_from = state, values_from = diff) %>%
## difference in differece bwetween states
mutate(diff_in_diff = NJ - PA)
## ---- message=FALSE---------------------------------------
## median difference-in-differences
minwage %>%
group_by(state) %>%
summarize(diff = median(fullPropAfter) - median(fullPropBefore)) %>%
pivot_wider(names_from = state, values_from = diff) %>%
mutate(diff_in_diff = NJ - PA)
## ---------------------------------------------------------
## summary() shows quartiles for the two wages variables
## as well as minimum, maximum, and mean
minwage %>%
filter(state == "NJ") %>% # just look at NJ
select(wageBefore, wageAfter) %>%
summary()
## The interquartile range
minwage %>%
filter(state == "NJ") %>%
select(wageBefore, wageAfter) %>%
summarize(wageBeforeIQR = IQR(wageBefore),
wageAfterIQR = IQR(wageAfter))
## ---------------------------------------------------------
## Create an object for the quantiles we want (deciles)
decile_probs <- seq(from = 0, to = 1, by = 0.1)
## Save deciles as characters
decile_names <- as.character(decile_probs)
## Generate the deciles for wage before and after
minwage %>%
filter(state == "NJ") %>%
select(wageBefore, wageAfter) %>%
summarize(wageBeforeDecile = quantile(wageBefore, probs = decile_probs),
wageAfterDecile = quantile(wageAfter, probs = decile_probs),
decile = decile_names)
## ---------------------------------------------------------
## Calculate the RMS of the change in full-time
## employment proportion in NJ
minwageNJ %>%
mutate(fullPropChange = fullPropAfter - fullPropBefore,
sqfullPropChange = fullPropChange^2) %>%
summarize(rms = sqrt(mean(sqfullPropChange)))
## Compare to the mean
minwageNJ %>%
mutate(fullPropChange = fullPropAfter - fullPropBefore) %>%
summarize(mean = mean(fullPropChange))
## ---- include=FALSE---------------------------------------
## Original, before corrections
minwage %>%
group_by(state) %>%
summarize_at(vars(wageAfter, wageBefore),
.funs = list(sd, var))
minwage %>%
group_by(state) %>%
summarize_at(vars(wageAfter, wageBefore),
.funs = list(stdv = sd,
variance = var))
## ---------------------------------------------------------
minwage %>%
group_by(state) %>%
summarize_at(vars(fullPropBefore, fullPropAfter),
.funs = list(sd, var))
minwage %>%
group_by(state) %>%
summarize_at(vars(fullPropBefore, fullPropAfter),
.funs = list(stdv = sd,
variance = var))
## ---- label = 'leader', echo = FALSE, warning=FALSE-------
data.frame("Name" = c("country", "year", "leadername", "age", "politybefore", "polityafter", "civilwarbefore", "civilwarafter", "interwarbefore", "interwarafter", "result"),
"Description" = c("country",
"year",
"name of leader who was targeted",
"age of the targeted leader",
"average polity score during the three-year period prior to the attempt",
"average polity score during the three-year period after the attempt",
"\\rexpr{1} if the country was in civil war during the three-year period prior to the attempt, \\rexpr{0} otherwise",
"\\rexpr{1} if the country was in civil war during the three-year period after the attempt, \\rexpr{0} otherwise",
"\\rexpr{1} if the country was in international war during the three-year period prior to the attempt, \\rexpr{0} otherwise",
"\\rexpr{1} if the country was in international war during the three-year period after the attempt, \\rexpr{0} otherwise",
"result of the assassination attempt")) %>%
mutate(Name = kableExtra::cell_spec(Name, monospace = TRUE)) %>%
knitr::kable(escape = FALSE, booktabs = TRUE, linesep = "", col.names = kableExtra::linebreak(c("\\textit{Variable}", "\\textit{Description}")), format.args = list(big.mark = ","), caption = 'Leader Assassination Data.') %>%
kableExtra::kable_styling() %>%
kableExtra::column_spec(2, width = "30em")
================================================
FILE: CAUSALITY/causality-tidy.Rmd
================================================
---
title: 'Code for QSS tidyverse Chapter 2: Causality'
author: "Kosuke Imai and Nora Webb Williams"
date: "First Printing"
output:
pdf_document: default
always_allow_html: true
---
# Causality
```{r setup2, include = FALSE, purl=FALSE, eval = T}
library(knitr)
library(kableExtra)
library(tidyverse)
opts_chunk$set(tidy = FALSE,
fig.align = "center",
background = "#EEEEEE",
fig.width = 7,
fig.height = 7,
out.width = ".7\\linewidth",
out.height = ".7\\linewidth",
cache = TRUE)
options(width = 60)
set.seed(12345)
```
## Racial Discrimination in the Labor Market
```{r, message=FALSE}
## Load required packages
library(tidyverse)
library(qss)
## Load in the data from QSS package
data(resume, package = "qss")
```
```{r}
## Or read in a saved CSV
resume <- read_csv("resume.csv")
```
```{r, message=FALSE}
resume <- read_csv("resume.csv",
col_types = cols(
firstname = col_character(),
sex = col_character(),
race = col_character(),
call = col_number()))
```
```{r}
dim(resume)
```
```{r}
head(resume)
tail(resume)
glimpse(resume)
```
```{r}
summary(resume)
```
```{r, message=FALSE}
race.call.summary <- resume %>%
group_by(race, call) %>% # create for each race and callback status
count()
race.call.summary
```
```{r, message=FALSE}
race.call.tab <- race.call.summary %>%
pivot_wider(names_from = call, # reshape the data
values_from = n)
race.call.tab
```
```{r}
race.call.tab.names <- race.call.tab %>%
rename(no_callback = "0",
callback = "1")
race.call.tab.names
```
```{r}
race.call.tab.names <- race.call.tab.names %>%
mutate(total_resumes = no_callback + callback,
callback_prop = callback / total_resumes)
race.call.tab.names
```
```{r}
overall_callback <- resume %>%
summarize(total_callback_rate = sum(call) / n())
overall_callback
```
```{r}
overall_callback <- resume %>%
summarize(total_callback_rate = mean(call))
overall_callback
```
```{r, message=FALSE}
callback_by_race <- resume %>%
group_by(race) %>%
summarize(callback_rate = mean(call))
callback_by_race
```
## Subsetting Data in R
### Logical Values and Operators
```{r}
class(TRUE)
```
```{r}
as.integer(TRUE)
as.integer(FALSE)
```
```{r}
x <- c(TRUE, FALSE, TRUE) # a vector with logical values
mean(x) # proportion of TRUEs
sum(x) # number of TRUEs
```
```{r}
FALSE & TRUE
TRUE & TRUE
```
```{r}
TRUE | FALSE
FALSE | FALSE
```
```{r}
TRUE & FALSE & TRUE
```
```{r}
(TRUE | FALSE) & FALSE # the parentheses evaluate to TRUE
TRUE | (FALSE & FALSE) # the parentheses evaluate to FALSE
```
```{r}
TF1 <- c(TRUE, FALSE, FALSE)
TF2 <- c(TRUE, FALSE, TRUE)
TF1 | TF2
TF1 & TF2
```
### Relational Operators
```{r}
4 > 3
"Hello" == "hello" # R is case-sensitive
"Hello" != "hello"
```
```{r}
x <- c(3, 2, 1, -2, -1)
x >= 2
x != 1
```
```{r}
## logical conjunction of two vectors with logical values
(x > 0) & (x <= 2)
## logical disjunction of two vectors with logical values
(x > 2) | (x <= -1)
```
```{r}
x.int <- (x > 0) & (x <= 2) # logical vector
x.int
mean(x.int) # proportion of TRUEs
sum(x.int) # number of TRUEs
```
### Subsetting
```{r}
## callback rate for black-sounding names
resume %>%
filter(race == "black") %>% # only keep observations where "race" is black
summarize(mean(call)) # take the average of call
```
```{r}
## Subset the data with black names
resumeB <- filter(resume, race == "black")
## Calculate the mean callback rate
summarize(resumeB, mean(call))
## with $ operator to run mean() on the call column
mean(resumeB$call)
```
```{r}
resumeBf <- filter(resume, race == "black" & sex == "female")
```
```{r}
## callback rate for black female names
Bf_callback <- filter(resume, race == "black" & sex == "female") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Bf_callback)
## callback rate for black male names
Bm_callback <- filter(resume, race == "black" & sex == "male") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Bm_callback)
## callback rate for white female names
Wf_callback <- filter(resume, race == "white" & sex == "female") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Wf_callback)
## callback rate for white male names
Wm_callback <- filter(resume, race == "white" & sex == "male") %>%
summarize(callback_rate = mean(call)) %>%
pull()
## print the value to the console
print(Wm_callback)
## difference between white women and black women
Wf_callback - Bf_callback
## difference between white men and black men
Wm_callback - Bm_callback
```
```{r, message=FALSE}
racial_gaps_by_sex <- resume %>%
group_by(race, sex) %>% # using two variables to group the data
summarize(callback = mean(call)) %>% # the callback rate for each group
pivot_wider(names_from = race, # reshaping the data
values_from = callback) %>%
mutate(race_gap = white - black)
print(racial_gaps_by_sex)
```
```{r, message=FALSE}
## what happens in this portion of the code?
resume %>%
group_by(race, sex) %>%
summarize(callback = mean(call))
## What happens after we add the pivot_wider()?
resume %>%
group_by(race, sex) %>%
summarize(callback = mean(call)) %>%
pivot_wider(names_from = race,
values_from = callback)
## And so on
```
### Simple Conditional Statements
```{r}
resume <- resume %>%
## create a new variable that is 1 if the resume is black and female,
## 0 otherwise
mutate(BlackFemale = if_else(race == "black" &
sex == "female", 1, 0))
```
```{r}
# Rows in the resumeBf data
nrow(resumeBf)
# Is that equal to sum of BlackFemale?
nrow(resumeBf) == resume %>% summarize(bf = sum(BlackFemale))
```
### Factor Variables
```{r}
resume_fact <- resume %>%
mutate(type = if_else(race == "black" & sex == "female", "BlackFemale", ""),
type = if_else(race == "black" & sex == "male", "BlackMale", type),
type = if_else(race == "white" & sex == "female", "WhiteFemale", type),
type = if_else(race == "white" & sex == "male", "WhiteMemale", type))
head(resume_fact)
```
```{r}
resume <- resume %>%
## add a categorical variable for race/gender type
mutate(type = case_when(race == "black" & sex == "female" ~ "BlackFemale",
race == "white" & sex == "female" ~ "WhiteFemale",
race == "black" & sex == "male" ~ "BlackMale",
race == "white" & sex == "male" ~ "WhiteMale",
TRUE ~ "other"
))
head(resume)
## Did any observations receive the "other" value for type?
filter(resume, type == "other")
```
```{r}
## check object class
class(resume$type)
## coerce the character variable into a factor variable
resume <- resume %>%
mutate(type = as.factor(type))
## look at the levels of the factor
levels(resume$type)
```
```{r, message=FALSE}
firstname_callback <- resume %>%
group_by(firstname) %>%
select(firstname, call) %>%
summarize(callback = mean(call))
head(firstname_callback)
```
## Causal Effects and the Counterfactual
```{r}
slice(resume, 1)
```
## Randomized Controlled Trials
### The Role of Randomization
### Social Pressure and Voter Turnout
```{r}
## Load in the data from QSS package
data(resume, package = "qss")
## Or from a csv
social <- read_csv("social.csv",
col_types = cols(sex = col_character(),
yearofbirth = col_double(),
primary2004 = col_double(),
messages = col_character(),
primary2006 = col_double(),
hhsize = col_double()))
summary(social) # summarize the data
```
```{r, message=FALSE}
## Average turnout by treatment message
turnout_by_message <- social %>%
group_by(messages) %>%
summarize(turnout = mean(primary2006))
turnout_by_message
## Differences between treatment(s) and control means
turnout_diffs <- turnout_by_message %>%
pivot_wider(names_from = messages,
values_from = turnout) %>%
mutate(diff_Civic_Duty = `Civic Duty` - Control,
diff_Hawthorne = Hawthorne - Control,
diff_Neighbors = Neighbors - Control) %>%
select(diff_Civic_Duty, diff_Hawthorne, diff_Neighbors)
turnout_diffs
```
```{r, message=FALSE}
social %>%
mutate(age = 2006 - yearofbirth) %>%
group_by(messages) %>%
summarize(age_avg = mean(age),
primary2004_avg = mean(primary2004),
hhsize_avg = mean(hhsize))
```
## Observational Studies
### Minimum Wage and Unemployment
```{r, message=FALSE}
minwage <- read_csv("minwage.csv") # load the data
## or
data(minwage, package = "qss")
dim(minwage) # dimension of data
glimpse(minwage)
summary(minwage) # summary of data
```
```{r, message=FALSE}
## Add a 'state' variable
minwage <- minwage %>%
mutate(state = if_else(location == "PA", "PA", "NJ"))
## Create the 'new_wage' object
new_wage <- 5.05
## Calculate the proportions above and below the new wage by state
state_props <- minwage %>%
mutate(above_min_before = if_else(wageBefore >= new_wage, 1, 0),
above_min_after = if_else(wageAfter >= new_wage, 1, 0)) %>%
group_by(state) %>%
summarize(prop_before = mean(above_min_before),
prop_after = mean(above_min_after))
state_props
```
```{r, message=FALSE}
## First create new variables to calculate the
## proportion of full-time employees
minwage <- minwage %>%
mutate(totalAfter = fullAfter + partAfter,
fullPropAfter = fullAfter / totalAfter)
## Then calculate the average proportion of full-time workers by state
full_prop_by_state <- minwage %>%
group_by(state) %>%
summarize(fullPropAfter = mean(fullPropAfter))
## To calculate the difference between states, we use pivot_wider()
## and mutate()
pivot_wider(full_prop_by_state,
names_from = state, values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
```
### Confounding Bias
```{r, message = FALSE}
chains_by_state <- minwage %>%
group_by(state) %>%
count(chain) %>%
mutate(prop = n / sum(n)) %>%
pivot_wider(-n, # this drops the 'n' variable prior to pivoting
names_from = state,
values_from = prop)
chains_by_state
```
```{r message=FALSE, warning=FALSE}
full_prop_by_state_chain <- minwage %>%
group_by(state, chain) %>%
summarize(fullPropAfter = mean(fullPropAfter)) %>%
pivot_wider(names_from = state,
values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
full_prop_by_state_chain
```
```{r, message = FALSE}
prop_by_state_chain_location_subset <- minwage %>%
filter(!location %in% c("shoreNJ", "centralNJ")) %>%
group_by(state, chain) %>%
summarize(fullPropAfter = mean(fullPropAfter)) %>%
pivot_wider(names_from = state,
values_from = fullPropAfter) %>%
mutate(diff = NJ - PA)
prop_by_state_chain_location_subset
```
### Before-and-After and Difference-in-Differences Designs
```{r}
## First, create a variable for the full-time
## proportion prior to the change
minwage <- minwage %>%
mutate(totalBefore = fullBefore + partBefore,
fullPropBefore = fullBefore / totalBefore)
## Then look at the differences in average proportion of full-time
## before and after (in NJ only)
minwage %>%
filter(state == "NJ") %>%
summarize(diff = mean(fullPropAfter) - mean(fullPropBefore))
```
```{r, message=FALSE}
## DiD estimate
minwage %>%
group_by(state) %>%
## difference before and after
summarize(diff = mean(fullPropAfter) - mean(fullPropBefore)) %>%
pivot_wider(names_from = state, values_from = diff) %>%
## difference in difference between states
mutate(diff_in_diff = NJ - PA)
```
## Descriptive Statistics for a Single Variable
### Quantiles
```{r, message=FALSE}
## median difference-in-differences
minwage %>%
group_by(state) %>%
summarize(diff = median(fullPropAfter) - median(fullPropBefore)) %>%
pivot_wider(names_from = state, values_from = diff) %>%
mutate(diff_in_diff = NJ - PA)
```
```{r}
## summary() shows quartiles for the two wages variables
## as well as minimum, maximum, and mean
minwage %>%
filter(state == "NJ") %>% # just look at NJ
select(wageBefore, wageAfter) %>%
summary()
## The interquartile range
minwage %>%
filter(state == "NJ") %>%
select(wageBefore, wageAfter) %>%
summarize(wageBeforeIQR = IQR(wageBefore),
wageAfterIQR = IQR(wageAfter))
```
```{r}
## Create an object for the quantiles we want (deciles)
decile_probs <- seq(from = 0, to = 1, by = 0.1)
## Save deciles as characters
decile_names <- as.character(decile_probs)
## Generate the deciles for wage before and after
minwage %>%
filter(state == "NJ") %>%
select(wageBefore, wageAfter) %>%
summarize(wageBeforeDecile = quantile(wageBefore, probs = decile_probs),
wageAfterDecile = quantile(wageAfter, probs = decile_probs),
decile = decile_names)
```
### Standard Deviation
```{r}
## Calculate the RMS of the change in full-time
## employment proportion in NJ
minwageNJ %>%
mutate(fullPropChange = fullPropAfter - fullPropBefore,
sqfullPropChange = fullPropChange^2) %>%
summarize(rms = sqrt(mean(sqfullPropChange)))
## Compare to the mean
minwageNJ %>%
mutate(fullPropChange = fullPropAfter - fullPropBefore) %>%
summarize(mean = mean(fullPropChange))
```
```{r, include=FALSE}
## Original, before corrections
minwage %>%
group_by(state) %>%
summarize_at(vars(wageAfter, wageBefore),
.funs = list(sd, var))
minwage %>%
group_by(state) %>%
summarize_at(vars(wageAfter, wageBefore),
.funs = list(stdv = sd,
variance = var))
```
```{r}
minwage %>%
group_by(state) %>%
summarize_at(vars(fullPropBefore, fullPropAfter),
.funs = list(sd, var))
minwage %>%
group_by(state) %>%
summarize_at(vars(fullPropBefore, fullPropAfter),
.funs = list(stdv = sd,
variance = var))
```
================================================
FILE: CAUSALITY/causality.R
================================================
## ------------------------------------------------------------------------
resume <- read.csv("resume.csv")
dim(resume)
head(resume)
summary(resume)
race.call.tab <- table(race = resume$race, call = resume$call)
race.call.tab
addmargins(race.call.tab)
## overall callback rate: total callbacks divided by the sample size
sum(race.call.tab[, 2]) / nrow(resume)
## callback rates for each race
race.call.tab[1, 2] / sum(race.call.tab[1, ]) # black
race.call.tab[2, 2] / sum(race.call.tab[2, ]) # white
race.call.tab[1, ] # the first row
race.call.tab[, 2] # the second column
mean(resume$call)
## ------------------------------------------------------------------------
class(TRUE)
as.integer(TRUE)
as.integer(FALSE)
x <- c(TRUE, FALSE, TRUE) # a vector with logical values
mean(x) # proportion of TRUEs
sum(x) # number of TRUEs
FALSE & TRUE
TRUE & TRUE
TRUE | FALSE
FALSE | FALSE
TRUE & FALSE & TRUE
(TRUE | FALSE) & FALSE # the parentheses evaluate to TRUE
TRUE | (FALSE & FALSE) # the parentheses evaluate to FALSE
TF1 <- c(TRUE, FALSE, FALSE)
TF2 <- c(TRUE, FALSE, TRUE)
TF1 | TF2
TF1 & TF2
## ------------------------------------------------------------------------
4 > 3
"Hello" == "hello" # R is case-sensitive
"Hello" != "hello"
x <- c(3, 2, 1, -2, -1)
x >= 2
x != 1
## logical conjunction of two vectors with logical values
(x > 0) & (x <= 2)
## logical disjunction of two vectors with logical values
(x > 2) | (x <= -1)
x.int <- (x > 0) & (x <= 2) # logical vector
x.int
mean(x.int) # proportion of TRUEs
sum(x.int) # number of TRUEs
## ------------------------------------------------------------------------
## callback rate for black-sounding names
mean(resume$call[resume$race == "black"])
## race of first 5 observations
resume$race[1:5]
## comparison of first 5 observations
(resume$race == "black")[1:5]
dim(resume) # dimension of original data frame
## subset blacks only
resumeB <- resume[resume$race == "black", ]
dim(resumeB) # this data.frame has fewer rows than the original data.frame
mean(resumeB$call) # callback rate for blacks
## keep "call" and "firstname" variables
## also keep observations with black female-sounding names
resumeBf <- subset(resume, select = c("call", "firstname"),
subset = (race == "black" & sex == "female"))
head(resumeBf)
## ## an alternative syntax with the same results
## resumeBf <- resume[resume$race == "black" & resume$sex == "female",
## c("call", "firstname")]
## black male
resumeBm <- subset(resume, subset = (race == "black") & (sex == "male"))
## white female
resumeWf <- subset(resume, subset = (race == "white") & (sex == "female"))
## white male
resumeWm <- subset(resume, subset = (race == "white") & (sex == "male"))
## racial gaps
mean(resumeWf$call) - mean(resumeBf$call) # among females
mean(resumeWm$call) - mean(resumeBm$call) # among males
## ------------------------------------------------------------------------
resume$BlackFemale <- ifelse(resume$race == "black" &
resume$sex == "female", 1, 0)
table(race = resume$race, sex = resume$sex,
BlackFemale = resume$BlackFemale)
## ------------------------------------------------------------------------
resume$type <- NA
resume$type[resume$race == "black" & resume$sex == "female"] <- "BlackFemale"
resume$type[resume$race == "black" & resume$sex == "male"] <- "BlackMale"
resume$type[resume$race == "white" & resume$sex == "female"] <- "WhiteFemale"
resume$type[resume$race == "white" & resume$sex == "male"] <- "WhiteMale"
## check object class
class(resume$type)
## coerce new character variable into a factor variable
resume$type <- as.factor(resume$type)
## list all levels of a factor variable
levels(resume$type)
## obtain the number of observations for each level
table(resume$type)
tapply(resume$call, resume$type, mean)
## turn first name into a factor variable
resume$firstname <- as.factor(resume$firstname)
## compute callback rate for each first name
callback.name <- tapply(resume$call, resume$firstname, mean)
## sort the result in the increasing order
sort(callback.name)
## ------------------------------------------------------------------------
resume[1, ]
## ------------------------------------------------------------------------
social <- read.csv("social.csv") # load the data
summary(social) # summarize the data
## turnout for each group
tapply(social$primary2006, social$messages, mean)
## turnout for control group
mean(social$primary2006[social$messages == "Control"])
## subtract control group turnout from each group
tapply(social$primary2006, social$messages, mean) -
mean(social$primary2006[social$messages == "Control"])
social$age <- 2006 - social$yearofbirth # create age variable
tapply(social$age, social$messages, mean)
tapply(social$primary2004, social$messages, mean)
tapply(social$hhsize, social$messages, mean)
## ------------------------------------------------------------------------
minwage <- read.csv("minwage.csv") # load the data
dim(minwage) # dimension of data
summary(minwage) # summary of data
## subsetting the data into two states
minwageNJ <- subset(minwage, subset = (location != "PA"))
minwagePA <- subset(minwage, subset = (location == "PA"))
## proportion of restaurants whose wage is less than $5.05
mean(minwageNJ$wageBefore < 5.05) # NJ before
mean(minwageNJ$wageAfter < 5.05) # NJ after
mean(minwagePA$wageBefore < 5.05) # PA before
mean(minwagePA$wageAfter < 5.05) # PA after
## create a variable for proportion of full-time employees in NJ and PA
minwageNJ$fullPropAfter <- minwageNJ$fullAfter /
(minwageNJ$fullAfter + minwageNJ$partAfter)
minwagePA$fullPropAfter <- minwagePA$fullAfter /
(minwagePA$fullAfter + minwagePA$partAfter)
## compute the difference in means
mean(minwageNJ$fullPropAfter) - mean(minwagePA$fullPropAfter)
## ------------------------------------------------------------------------
prop.table(table(minwageNJ$chain))
prop.table(table(minwagePA$chain))
## subset Burger King only
minwageNJ.bk <- subset(minwageNJ, subset = (chain == "burgerking"))
minwagePA.bk <- subset(minwagePA, subset = (chain == "burgerking"))
## comparison of full-time employment rates
mean(minwageNJ.bk$fullPropAfter) - mean(minwagePA.bk$fullPropAfter)
minwageNJ.bk.subset <-
subset(minwageNJ.bk, subset = ((location != "shoreNJ") &
(location != "centralNJ")))
mean(minwageNJ.bk.subset$fullPropAfter) - mean(minwagePA.bk$fullPropAfter)
## ------------------------------------------------------------------------
## full-time employment proportion in the previous period for NJ
minwageNJ$fullPropBefore <- minwageNJ$fullBefore /
(minwageNJ$fullBefore + minwageNJ$partBefore)
## mean difference between before and after the minimum wage increase
NJdiff <- mean(minwageNJ$fullPropAfter) - mean(minwageNJ$fullPropBefore)
NJdiff
## full-time employment proportion in the previous period for PA
minwagePA$fullPropBefore <- minwagePA$fullBefore /
(minwagePA$fullBefore + minwagePA$partBefore)
## mean difference between before and after for PA
PAdiff <- mean(minwagePA$fullPropAfter) - mean(minwagePA$fullPropBefore)
## difference-in-differences
NJdiff - PAdiff
## full-time employment proportion in the previous period for PA
minwagePA$fullPropBefore <- minwagePA$fullBefore /
(minwagePA$fullBefore + minwagePA$partBefore)
## mean difference between before and after for PA
PAdiff <- mean(minwagePA$fullPropAfter) - mean(minwagePA$fullPropBefore)
## difference-in-differences
NJdiff - PAdiff
## ------------------------------------------------------------------------
## cross-section comparison between NJ and PA
median(minwageNJ$fullPropAfter) - median(minwagePA$fullPropAfter)
## before and after comparison
NJdiff.med <- median(minwageNJ$fullPropAfter) -
median(minwageNJ$fullPropBefore)
NJdiff.med
## median difference-in-differences
PAdiff.med <- median(minwagePA$fullPropAfter) -
median(minwagePA$fullPropBefore)
NJdiff.med - PAdiff.med
## summary shows quartiles as well as minimum, maximum, and mean
summary(minwageNJ$wageBefore)
summary(minwageNJ$wageAfter)
## interquartile range
IQR(minwageNJ$wageBefore)
IQR(minwageNJ$wageAfter)
## deciles (10 groups)
quantile(minwageNJ$wageBefore, probs = seq(from = 0, to = 1, by = 0.1))
quantile(minwageNJ$wageAfter, probs = seq(from = 0, to = 1, by = 0.1))
## ------------------------------------------------------------------------
sqrt(mean((minwageNJ$fullPropAfter - minwageNJ$fullPropBefore)^2))
mean(minwageNJ$fullPropAfter - minwageNJ$fullPropBefore)
## standard deviation
sd(minwageNJ$fullPropBefore)
sd(minwageNJ$fullPropAfter)
## variance
var(minwageNJ$fullPropBefore)
var(minwageNJ$fullPropAfter)
================================================
FILE: CAUSALITY/causality.Rmd
================================================
---
title: 'Code for QSS Chapter 2: Causality'
author: "Kosuke Imai"
date: "First Printing"
output:
pdf_document: default
---
# Section 2.1: Racial Discrimination in the Labor Market
```{r}
resume <- read.csv("resume.csv")
dim(resume)
head(resume)
summary(resume)
race.call.tab <- table(race = resume$race, call = resume$call)
race.call.tab
addmargins(race.call.tab)
## overall callback rate: total callbacks divided by the sample size
sum(race.call.tab[, 2]) / nrow(resume)
## callback rates for each race
race.call.tab[1, 2] / sum(race.call.tab[1, ]) # black
race.call.tab[2, 2] / sum(race.call.tab[2, ]) # white
race.call.tab[1, ] # the first row
race.call.tab[, 2] # the second column
mean(resume$call)
```
# Section 2.2: Subsetting the Data in R
```{r}
class(TRUE)
as.integer(TRUE)
as.integer(FALSE)
x <- c(TRUE, FALSE, TRUE) # a vector with logical values
mean(x) # proportion of TRUEs
sum(x) # number of TRUEs
FALSE & TRUE
TRUE & TRUE
TRUE | FALSE
FALSE | FALSE
TRUE & FALSE & TRUE
(TRUE | FALSE) & FALSE # the parentheses evaluate to TRUE
TRUE | (FALSE & FALSE) # the parentheses evaluate to FALSE
TF1 <- c(TRUE, FALSE, FALSE)
TF2 <- c(TRUE, FALSE, TRUE)
TF1 | TF2
TF1 & TF2
```
## Section 2.2.2: Relational Operators
```{r}
4 > 3
"Hello" == "hello" # R is case-sensitive
"Hello" != "hello"
x <- c(3, 2, 1, -2, -1)
x >= 2
x != 1
## logical conjunction of two vectors with logical values
(x > 0) & (x <= 2)
## logical disjunction of two vectors with logical values
(x > 2) | (x <= -1)
x.int <- (x > 0) & (x <= 2) # logical vector
x.int
mean(x.int) # proportion of TRUEs
sum(x.int) # number of TRUEs
```
## Section 2.2.3: Subsetting
```{r}
## callback rate for black-sounding names
mean(resume$call[resume$race == "black"])
## race of first 5 observations
resume$race[1:5]
## comparison of first 5 observations
(resume$race == "black")[1:5]
dim(resume) # dimension of original data frame
## subset blacks only
resumeB <- resume[resume$race == "black", ]
dim(resumeB) # this data.frame has fewer rows than the original data.frame
mean(resumeB$call) # callback rate for blacks
## keep "call" and "firstname" variables
## also keep observations with black female-sounding names
resumeBf <- subset(resume, select = c("call", "firstname"),
subset = (race == "black" & sex == "female"))
head(resumeBf)
## ## an alternative syntax with the same results
## resumeBf <- resume[resume$race == "black" & resume$sex == "female",
## c("call", "firstname")]
## black male
resumeBm <- subset(resume, subset = (race == "black") & (sex == "male"))
## white female
resumeWf <- subset(resume, subset = (race == "white") & (sex == "female"))
## white male
resumeWm <- subset(resume, subset = (race == "white") & (sex == "male"))
## racial gaps
mean(resumeWf$call) - mean(resumeBf$call) # among females
mean(resumeWm$call) - mean(resumeBm$call) # among males
```
## Section 2.2.4: Simple Conditional Statements
```{r}
resume$BlackFemale <- ifelse(resume$race == "black" &
resume$sex == "female", 1, 0)
table(race = resume$race, sex = resume$sex,
BlackFemale = resume$BlackFemale)
```
## Section 2.2.5: Factor Variables
```{r}
resume$type <- NA
resume$type[resume$race == "black" & resume$sex == "female"] <- "BlackFemale"
resume$type[resume$race == "black" & resume$sex == "male"] <- "BlackMale"
resume$type[resume$race == "white" & resume$sex == "female"] <- "WhiteFemale"
resume$type[resume$race == "white" & resume$sex == "male"] <- "WhiteMale"
## check object class
class(resume$type)
## coerce new character variable into a factor variable
resume$type <- as.factor(resume$type)
## list all levels of a factor variable
levels(resume$type)
## obtain the number of observations for each level
table(resume$type)
tapply(resume$call, resume$type, mean)
## turn first name into a factor variable
resume$firstname <- as.factor(resume$firstname)
## compute callback rate for each first name
callback.name <- tapply(resume$call, resume$firstname, mean)
## sort the result in the increasing order
sort(callback.name)
```
# Section 2.3: Causal Effects and the Counterfactual
```{r}
resume[1, ]
```
# Section 2.4: Randomized Controlled Trials
## Section 2.4.1: The Role of Randomization
## Section 2.4.2: Social Pressure and Voter Turnout
```{r}
social <- read.csv("social.csv") # load the data
summary(social) # summarize the data
## turnout for each group
tapply(social$primary2006, social$messages, mean)
## turnout for control group
mean(social$primary2006[social$messages == "Control"])
## subtract control group turnout from each group
tapply(social$primary2006, social$messages, mean) -
mean(social$primary2006[social$messages == "Control"])
social$age <- 2006 - social$yearofbirth # create age variable
tapply(social$age, social$messages, mean)
tapply(social$primary2004, social$messages, mean)
tapply(social$hhsize, social$messages, mean)
```
# Section 2.5: Observational Studies
## Section 2.5.1: Minimum Wage and Unemployment
```{r}
minwage <- read.csv("minwage.csv") # load the data
dim(minwage) # dimension of data
summary(minwage) # summary of data
## subsetting the data into two states
minwageNJ <- subset(minwage, subset = (location != "PA"))
minwagePA <- subset(minwage, subset = (location == "PA"))
## proportion of restaurants whose wage is less than $5.05
mean(minwageNJ$wageBefore < 5.05) # NJ before
mean(minwageNJ$wageAfter < 5.05) # NJ after
mean(minwagePA$wageBefore < 5.05) # PA before
mean(minwagePA$wageAfter < 5.05) # PA after
## create a variable for proportion of full-time employees in NJ and PA
minwageNJ$fullPropAfter <- minwageNJ$fullAfter /
(minwageNJ$fullAfter + minwageNJ$partAfter)
minwagePA$fullPropAfter <- minwagePA$fullAfter /
(minwagePA$fullAfter + minwagePA$partAfter)
## compute the difference in means
mean(minwageNJ$fullPropAfter) - mean(minwagePA$fullPropAfter)
```
## Section 2.5.2: Confounding Bias
```{r}
prop.table(table(minwageNJ$chain))
prop.table(table(minwagePA$chain))
## subset Burger King only
minwageNJ.bk <- subset(minwageNJ, subset = (chain == "burgerking"))
minwagePA.bk <- subset(minwagePA, subset = (chain == "burgerking"))
## comparison of full-time employment rates
mean(minwageNJ.bk$fullPropAfter) - mean(minwagePA.bk$fullPropAfter)
minwageNJ.bk.subset <-
subset(minwageNJ.bk, subset = ((location != "shoreNJ") &
(location != "centralNJ")))
mean(minwageNJ.bk.subset$fullPropAfter) - mean(minwagePA.bk$fullPropAfter)
```
## Section 2.5.3: Before-and-After and Difference-in-Differences Designs
```{r}
## full-time employment proportion in the previous period for NJ
minwageNJ$fullPropBefore <- minwageNJ$fullBefore /
(minwageNJ$fullBefore + minwageNJ$partBefore)
## mean difference between before and after the minimum wage increase
NJdiff <- mean(minwageNJ$fullPropAfter) - mean(minwageNJ$fullPropBefore)
NJdiff
## full-time employment proportion in the previous period for PA
minwagePA$fullPropBefore <- minwagePA$fullBefore /
(minwagePA$fullBefore + minwagePA$partBefore)
## mean difference between before and after for PA
PAdiff <- mean(minwagePA$fullPropAfter) - mean(minwagePA$fullPropBefore)
## difference-in-differences
NJdiff - PAdiff
## full-time employment proportion in the previous period for PA
minwagePA$fullPropBefore <- minwagePA$fullBefore /
(minwagePA$fullBefore + minwagePA$partBefore)
## mean difference between before and after for PA
PAdiff <- mean(minwagePA$fullPropAfter) - mean(minwagePA$fullPropBefore)
## difference-in-differences
NJdiff - PAdiff
```
# Section 2.6: Descriptive Statistics for a Single Variable
## Section 2.6.1: Quantiles
```{r}
## cross-section comparison between NJ and PA
median(minwageNJ$fullPropAfter) - median(minwagePA$fullPropAfter)
## before and after comparison
NJdiff.med <- median(minwageNJ$fullPropAfter) -
median(minwageNJ$fullPropBefore)
NJdiff.med
## median difference-in-differences
PAdiff.med <- median(minwagePA$fullPropAfter) -
median(minwagePA$fullPropBefore)
NJdiff.med - PAdiff.med
## summary shows quartiles as well as minimum, maximum, and mean
summary(minwageNJ$wageBefore)
summary(minwageNJ$wageAfter)
## interquartile range
IQR(minwageNJ$wageBefore)
IQR(minwageNJ$wageAfter)
## deciles (10 groups)
quantile(minwageNJ$wageBefore, probs = seq(from = 0, to = 1, by = 0.1))
quantile(minwageNJ$wageAfter, probs = seq(from = 0, to = 1, by = 0.1))
```
## 2.6.2: Standard Deviation
```{r}
sqrt(mean((minwageNJ$fullPropAfter - minwageNJ$fullPropBefore)^2))
mean(minwageNJ$fullPropAfter - minwageNJ$fullPropBefore)
## standard deviation
sd(minwageNJ$fullPropBefore)
sd(minwageNJ$fullPropAfter)
## variance
var(minwageNJ$fullPropBefore)
var(minwageNJ$fullPropAfter)
```
================================================
FILE: CAUSALITY/gay.csv
================================================
study,treatment,wave,ssm
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,7,5
1,No Contact,7,5
1,No Contact,6,4
1,No Contact,1,4
1,No Contact,2,4
1,No Contact,5,5
1,No Contact,3,3
1,No Contact,4,4
1,No Contact,6,5
1,No Contact,2,3
1,No Contact,1,5
1,No Contact,4,4
1,No Contact,5,5
1,No Contact,7,5
1,No Contact,6,4
1,No Contact,3,4
1,No Contact,1,4
1,No Contact,5,4
1,No Contact,2,3
1,Recycling Script by Gay Canvasser,4,1
1,Recycling Script by Gay Canvasser,2,2
1,Recycling Script by Gay Canvasser,7,1
1,Recycling Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,3,2
1,No Contact,4,5
1,No Contact,6,5
1,No Contact,7,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,2,4
1,No Contact,1,5
1,No Contact,5,2
1,No Contact,3,3
1,No Contact,2,3
1,No Contact,6,3
1,No Contact,1,3
1,No Contact,1,2
1,No Contact,4,2
1,No Contact,3,2
1,No Contact,6,2
1,No Contact,2,2
1,No Contact,7,2
1,No Contact,5,2
1,No Contact,7,4
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,2,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,1,4
1,No Contact,3,5
1,No Contact,2,4
1,No Contact,4,4
1,No Contact,6,4
1,No Contact,4,1
1,No Contact,7,3
1,No Contact,1,1
1,No Contact,6,2
1,No Contact,5,2
1,No Contact,3,1
1,No Contact,2,1
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,2,5
2,No Contact,1,1
2,No Contact,7,2
2,No Contact,2,2
2,No Contact,3,2
2,No Contact,4,1
2,No Contact,2,3
2,No Contact,7,5
2,No Contact,3,4
2,No Contact,1,3
2,No Contact,4,2
2,Same-Sex Marriage Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,3,1
2,Same-Sex Marriage Script by Gay Canvasser,2,1
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,3,4
2,Same-Sex Marriage Script by Gay Canvasser,7,4
2,Same-Sex Marriage Script by Gay Canvasser,4,4
1,No Contact,5,3
1,No Contact,6,3
1,No Contact,4,3
1,No Contact,1,3
1,No Contact,2,3
1,No Contact,3,3
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,2,4
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,7,4
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,2,5
1,No Contact,2,1
1,No Contact,5,2
1,No Contact,6,2
1,No Contact,3,1
1,No Contact,1,1
1,No Contact,7,1
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
1,No Contact,2,5
1,No Contact,5,5
1,No Contact,4,5
1,No Contact,6,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,7,1
1,No Contact,1,1
1,No Contact,5,2
1,No Contact,4,1
1,No Contact,6,1
1,No Contact,3,2
1,No Contact,2,1
1,No Contact,1,2
1,No Contact,4,2
1,No Contact,2,2
1,No Contact,3,2
1,No Contact,5,1
1,No Contact,2,3
1,No Contact,6,4
1,No Contact,7,5
1,No Contact,4,4
1,No Contact,3,3
1,No Contact,5,4
1,No Contact,1,4
1,No Contact,5,2
1,No Contact,7,4
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,2,1
1,No Contact,4,2
1,No Contact,2,5
1,No Contact,7,4
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,4,4
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,2,4
1,No Contact,5,5
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,7,4
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,2,4
2,No Contact,3,4
2,No Contact,1,3
2,No Contact,2,4
2,No Contact,4,2
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,4,1
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,5,1
1,No Contact,6,2
1,No Contact,7,3
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,5,1
1,Recycling Script by Straight Canvasser,6,2
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,2,1
1,No Contact,4,3
1,No Contact,7,3
1,No Contact,1,3
1,No Contact,6,3
1,No Contact,5,3
1,No Contact,3,3
1,No Contact,2,4
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,7,4
1,No Contact,5,5
1,No Contact,2,2
1,No Contact,7,2
1,No Contact,4,2
1,No Contact,6,3
1,No Contact,1,2
1,No Contact,5,3
1,No Contact,1,5
1,No Contact,5,5
1,No Contact,2,4
1,No Contact,6,5
1,No Contact,4,5
2,Same-Sex Marriage Script by Gay Canvasser,7,1
2,Same-Sex Marriage Script by Gay Canvasser,3,1
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,2,1
2,Same-Sex Marriage Script by Gay Canvasser,1,1
1,No Contact,4,4
1,No Contact,1,4
1,No Contact,3,4
1,No Contact,2,5
1,No Contact,7,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,5,4
1,No Contact,4,5
2,Same-Sex Marriage Script by Gay Canvasser,3,1
2,Same-Sex Marriage Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,2,1
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,2,2
2,Same-Sex Marriage Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,7,2
1,No Contact,6,4
1,No Contact,4,4
1,No Contact,2,3
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,1,4
1,No Contact,5,1
1,No Contact,7,1
1,No Contact,3,1
1,No Contact,2,2
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,5,2
1,No Contact,2,1
1,No Contact,4,1
1,No Contact,6,2
1,No Contact,3,1
1,No Contact,7,1
1,No Contact,7,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,4,5
1,No Contact,7,5
1,No Contact,3,5
1,No Contact,2,4
1,No Contact,3,5
1,No Contact,6,4
1,No Contact,4,4
1,No Contact,5,5
1,No Contact,1,4
1,Same-Sex Marriage Script by Gay Canvasser,6,4
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,4,3
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,3,4
1,Same-Sex Marriage Script by Gay Canvasser,1,4
1,Recycling Script by Gay Canvasser,1,4
1,Recycling Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,6,4
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,7,4
1,Recycling Script by Gay Canvasser,2,4
1,No Contact,5,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,2,5
1,No Contact,6,5
1,No Contact,3,1
1,No Contact,5,2
1,No Contact,6,2
1,No Contact,2,1
1,No Contact,4,1
1,No Contact,1,1
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,4
2,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,3,2
1,Same-Sex Marriage Script by Straight Canvasser,6,2
1,Same-Sex Marriage Script by Straight Canvasser,1,2
1,Same-Sex Marriage Script by Straight Canvasser,7,2
1,Same-Sex Marriage Script by Straight Canvasser,4,2
1,Same-Sex Marriage Script by Straight Canvasser,5,3
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,3,3
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,7,2
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,5,1
1,No Contact,2,4
1,No Contact,4,5
1,No Contact,6,4
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,7,5
1,No Contact,4,4
1,No Contact,2,5
1,No Contact,6,5
1,No Contact,5,5
1,No Contact,4,4
1,No Contact,1,4
1,No Contact,7,4
1,No Contact,3,4
1,No Contact,6,4
1,No Contact,2,3
1,No Contact,1,3
1,No Contact,2,3
1,No Contact,4,2
1,No Contact,6,3
1,No Contact,3,3
1,No Contact,5,4
1,No Contact,4,1
1,No Contact,3,2
1,No Contact,5,1
1,No Contact,7,2
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,2,5
1,No Contact,3,4
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,2,1
1,No Contact,1,1
1,No Contact,4,2
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,5,4
1,No Contact,3,4
1,No Contact,2,4
1,No Contact,7,3
1,No Contact,6,3
1,No Contact,4,4
1,No Contact,5,1
1,No Contact,3,3
1,No Contact,1,3
1,No Contact,2,3
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,4,1
1,Recycling Script by Gay Canvasser,2,1
1,Recycling Script by Gay Canvasser,5,1
1,No Contact,6,5
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,4,4
1,No Contact,5,5
1,No Contact,1,1
1,No Contact,2,1
1,No Contact,3,2
1,No Contact,4,2
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,5,4
1,No Contact,4,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,6,5
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,7,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Gay Canvasser,3,2
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,2,2
1,Recycling Script by Gay Canvasser,5,1
1,No Contact,3,1
1,No Contact,7,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,5,2
1,No Contact,6,1
2,No Contact,7,1
2,No Contact,2,1
2,No Contact,1,1
2,No Contact,4,1
1,Same-Sex Marriage Script by Straight Canvasser,3,3
1,Same-Sex Marriage Script by Straight Canvasser,1,3
1,Same-Sex Marriage Script by Straight Canvasser,2,3
1,Same-Sex Marriage Script by Straight Canvasser,7,3
1,Same-Sex Marriage Script by Straight Canvasser,6,3
1,Same-Sex Marriage Script by Straight Canvasser,5,3
1,Same-Sex Marriage Script by Straight Canvasser,4,3
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,2,5
1,No Contact,7,3
1,No Contact,3,4
1,No Contact,1,5
1,No Contact,4,2
1,No Contact,2,3
1,No Contact,3,2
1,No Contact,5,1
1,No Contact,6,3
1,No Contact,7,3
1,No Contact,1,2
1,No Contact,2,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,4,4
2,No Contact,3,4
2,No Contact,7,5
2,No Contact,4,5
2,No Contact,1,5
2,No Contact,2,5
2,No Contact,1,5
2,No Contact,3,4
2,No Contact,2,5
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
2,No Contact,3,5
2,No Contact,7,5
2,No Contact,1,5
2,No Contact,4,5
2,No Contact,2,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,6,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,2,4
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,5,5
2,No Contact,2,2
2,No Contact,3,1
2,No Contact,4,1
2,No Contact,1,1
1,No Contact,3,2
1,No Contact,4,2
1,No Contact,2,2
1,No Contact,1,2
1,No Contact,5,2
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
1,No Contact,4,2
1,No Contact,1,2
1,No Contact,6,2
1,No Contact,2,2
1,No Contact,3,3
1,No Contact,7,3
1,No Contact,5,2
1,No Contact,5,4
1,No Contact,3,5
1,No Contact,2,4
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,3,3
1,No Contact,5,4
1,No Contact,2,3
1,No Contact,4,4
1,No Contact,6,3
1,No Contact,1,3
1,No Contact,4,5
1,No Contact,7,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,7,5
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,2,4
1,Same-Sex Marriage Script by Straight Canvasser,4,1
1,Same-Sex Marriage Script by Straight Canvasser,2,2
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,No Contact,3,2
1,No Contact,1,1
1,No Contact,7,2
1,No Contact,6,1
1,No Contact,6,1
1,No Contact,7,1
1,No Contact,5,1
1,No Contact,1,1
1,No Contact,4,2
1,No Contact,3,1
1,No Contact,1,1
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,2,1
1,No Contact,7,1
2,No Contact,1,5
2,No Contact,4,5
2,No Contact,2,5
2,No Contact,7,5
2,No Contact,3,5
1,Recycling Script by Straight Canvasser,2,5
1,Recycling Script by Straight Canvasser,7,5
1,Recycling Script by Straight Canvasser,5,5
1,Recycling Script by Straight Canvasser,1,4
1,Recycling Script by Straight Canvasser,3,4
1,Recycling Script by Straight Canvasser,4,4
1,Recycling Script by Straight Canvasser,6,4
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,No Contact,3,1
1,No Contact,1,1
1,No Contact,2,1
1,No Contact,7,1
1,No Contact,6,1
1,No Contact,5,1
1,No Contact,2,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,7,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,6,5
1,Recycling Script by Straight Canvasser,5,1
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,7,4
2,No Contact,2,5
2,No Contact,1,5
2,No Contact,3,5
2,No Contact,7,5
2,No Contact,4,4
2,No Contact,7,5
2,No Contact,4,5
2,No Contact,2,4
2,No Contact,3,5
2,No Contact,1,5
1,No Contact,1,4
1,No Contact,4,5
1,No Contact,2,4
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,4,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,7,5
1,Recycling Script by Straight Canvasser,6,2
1,Recycling Script by Straight Canvasser,2,2
1,Recycling Script by Straight Canvasser,7,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,6,1
1,Same-Sex Marriage Script by Straight Canvasser,2,1
1,Same-Sex Marriage Script by Straight Canvasser,5,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,Same-Sex Marriage Script by Straight Canvasser,4,1
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Recycling Script by Straight Canvasser,2,5
1,Recycling Script by Straight Canvasser,7,5
1,Recycling Script by Straight Canvasser,3,5
1,Recycling Script by Straight Canvasser,1,5
1,Recycling Script by Straight Canvasser,4,5
1,Recycling Script by Straight Canvasser,6,5
1,Recycling Script by Straight Canvasser,5,4
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,6,5
1,No Contact,7,4
1,No Contact,6,1
1,No Contact,5,3
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,2,1
1,No Contact,3,1
1,No Contact,2,2
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,7,1
1,No Contact,4,2
1,No Contact,5,1
1,No Contact,5,2
1,No Contact,6,3
1,No Contact,4,3
1,No Contact,3,3
1,No Contact,1,3
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Straight Canvasser,6,2
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,7,2
1,Recycling Script by Straight Canvasser,1,2
1,Same-Sex Marriage Script by Gay Canvasser,6,1
1,Same-Sex Marriage Script by Gay Canvasser,7,1
1,Same-Sex Marriage Script by Gay Canvasser,4,1
1,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Same-Sex Marriage Script by Gay Canvasser,3,1
1,Same-Sex Marriage Script by Gay Canvasser,2,1
1,No Contact,2,2
1,No Contact,4,2
1,No Contact,5,3
1,No Contact,6,2
1,No Contact,1,2
2,No Contact,3,1
2,No Contact,4,1
2,No Contact,1,1
2,No Contact,2,1
2,No Contact,7,1
1,Same-Sex Marriage Script by Straight Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,2,5
1,Same-Sex Marriage Script by Straight Canvasser,5,4
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,Same-Sex Marriage Script by Straight Canvasser,6,5
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,5,1
1,Same-Sex Marriage Script by Straight Canvasser,2,2
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,7,1
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,4,2
1,No Contact,2,1
1,No Contact,3,1
1,No Contact,6,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,5,2
1,No Contact,7,3
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,2,1
1,No Contact,5,2
1,No Contact,3,1
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,6,1
1,No Contact,3,5
1,No Contact,2,5
1,No Contact,1,5
1,No Contact,5,4
1,No Contact,4,4
1,No Contact,5,4
1,No Contact,4,2
1,No Contact,3,3
1,No Contact,1,2
1,No Contact,7,3
1,No Contact,6,2
1,No Contact,7,1
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,5,1
1,No Contact,4,1
1,No Contact,1,1
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,2,4
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,7,3
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,5,2
1,No Contact,6,2
1,No Contact,7,1
1,No Contact,2,2
1,No Contact,5,3
1,No Contact,4,2
1,No Contact,1,2
1,No Contact,3,2
1,Same-Sex Marriage Script by Straight Canvasser,1,3
1,Same-Sex Marriage Script by Straight Canvasser,5,4
1,Same-Sex Marriage Script by Straight Canvasser,4,3
1,Same-Sex Marriage Script by Straight Canvasser,2,2
1,Same-Sex Marriage Script by Straight Canvasser,6,3
1,Same-Sex Marriage Script by Straight Canvasser,3,3
1,Same-Sex Marriage Script by Straight Canvasser,7,1
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,2,1
1,Same-Sex Marriage Script by Straight Canvasser,5,1
1,Same-Sex Marriage Script by Straight Canvasser,6,1
1,Same-Sex Marriage Script by Straight Canvasser,4,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,Same-Sex Marriage Script by Straight Canvasser,2,5
1,Same-Sex Marriage Script by Straight Canvasser,6,5
1,Same-Sex Marriage Script by Straight Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,Same-Sex Marriage Script by Straight Canvasser,5,5
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,4,4
1,Same-Sex Marriage Script by Straight Canvasser,2,4
1,Same-Sex Marriage Script by Straight Canvasser,1,4
1,Same-Sex Marriage Script by Straight Canvasser,5,4
1,Same-Sex Marriage Script by Straight Canvasser,3,4
1,Same-Sex Marriage Script by Straight Canvasser,7,4
1,Same-Sex Marriage Script by Straight Canvasser,6,4
1,No Contact,1,1
1,No Contact,7,1
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,6,1
1,No Contact,6,5
1,No Contact,7,5
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,4,4
1,No Contact,6,3
1,No Contact,7,4
1,No Contact,4,2
1,No Contact,1,2
1,No Contact,3,2
1,No Contact,2,2
1,No Contact,1,5
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,7,4
1,No Contact,6,5
1,No Contact,2,5
2,Same-Sex Marriage Script by Gay Canvasser,3,1
2,Same-Sex Marriage Script by Gay Canvasser,2,1
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,1,1
1,No Contact,3,4
1,No Contact,2,3
1,No Contact,4,4
1,No Contact,1,4
1,No Contact,6,4
2,No Contact,2,5
2,No Contact,1,5
2,No Contact,7,5
2,No Contact,3,5
2,No Contact,4,5
1,No Contact,7,1
1,No Contact,5,2
1,No Contact,1,1
1,No Contact,4,2
1,No Contact,2,1
1,No Contact,6,1
1,No Contact,3,1
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,No Contact,1,5
2,No Contact,3,5
2,No Contact,4,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,5,5
1,Same-Sex Marriage Script by Straight Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,6,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,6,1
1,Same-Sex Marriage Script by Straight Canvasser,2,1
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,5,2
1,Same-Sex Marriage Script by Straight Canvasser,7,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,Same-Sex Marriage Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,7,1
1,Recycling Script by Straight Canvasser,2,1
1,Recycling Script by Straight Canvasser,6,1
1,Recycling Script by Straight Canvasser,1,1
1,Recycling Script by Straight Canvasser,4,1
1,Recycling Script by Straight Canvasser,5,1
1,Recycling Script by Straight Canvasser,3,2
2,No Contact,7,1
2,No Contact,3,1
2,No Contact,4,1
2,No Contact,1,1
2,No Contact,2,1
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,2,3
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,6,1
1,No Contact,2,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,7,4
1,No Contact,5,2
1,No Contact,2,1
1,No Contact,6,1
1,No Contact,5,1
1,No Contact,7,1
1,No Contact,3,1
1,No Contact,1,1
1,Same-Sex Marriage Script by Straight Canvasser,2,3
1,Same-Sex Marriage Script by Straight Canvasser,1,3
1,Same-Sex Marriage Script by Straight Canvasser,5,3
1,Same-Sex Marriage Script by Straight Canvasser,3,3
1,Same-Sex Marriage Script by Straight Canvasser,4,3
1,No Contact,6,5
1,No Contact,5,5
1,No Contact,4,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,2,5
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,No Contact,6,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,7,5
2,Same-Sex Marriage Script by Gay Canvasser,1,2
2,Same-Sex Marriage Script by Gay Canvasser,4,1
2,Same-Sex Marriage Script by Gay Canvasser,2,3
2,Same-Sex Marriage Script by Gay Canvasser,3,2
2,Same-Sex Marriage Script by Gay Canvasser,7,1
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,2,2
2,Same-Sex Marriage Script by Gay Canvasser,7,2
2,Same-Sex Marriage Script by Gay Canvasser,4,2
1,No Contact,4,5
1,No Contact,3,4
1,No Contact,2,5
1,No Contact,6,5
1,No Contact,5,5
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,3,4
1,No Contact,4,4
1,No Contact,7,5
1,No Contact,2,4
1,No Contact,6,4
1,No Contact,5,3
1,No Contact,1,4
1,Recycling Script by Straight Canvasser,2,2
1,Recycling Script by Straight Canvasser,6,3
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,5,1
1,Recycling Script by Straight Canvasser,7,2
1,Recycling Script by Straight Canvasser,1,2
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,6,4
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,2,4
1,Recycling Script by Gay Canvasser,1,4
1,Recycling Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,6,3
1,Recycling Script by Gay Canvasser,4,3
1,Recycling Script by Gay Canvasser,2,3
1,Recycling Script by Gay Canvasser,5,3
1,Recycling Script by Gay Canvasser,7,3
1,Recycling Script by Gay Canvasser,1,3
1,Recycling Script by Gay Canvasser,4,1
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,3,1
1,Recycling Script by Gay Canvasser,2,1
1,Recycling Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,7,3
2,Same-Sex Marriage Script by Gay Canvasser,2,5
1,No Contact,5,4
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,7,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,2,5
1,No Contact,1,5
1,No Contact,3,2
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,2,1
1,No Contact,7,1
1,No Contact,6,1
1,Recycling Script by Gay Canvasser,2,5
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,4,5
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,7,2
1,Recycling Script by Gay Canvasser,4,2
1,Recycling Script by Gay Canvasser,2,2
1,Recycling Script by Gay Canvasser,1,2
1,Recycling Script by Gay Canvasser,3,2
1,Recycling Script by Gay Canvasser,6,2
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,4,5
1,Recycling Script by Gay Canvasser,2,5
1,Recycling Script by Gay Canvasser,2,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,4,5
1,Recycling Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,6,5
1,Same-Sex Marriage Script by Straight Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,Recycling Script by Gay Canvasser,3,2
1,Recycling Script by Gay Canvasser,6,2
1,Recycling Script by Gay Canvasser,1,2
1,Recycling Script by Gay Canvasser,5,1
1,Recycling Script by Gay Canvasser,2,2
1,Recycling Script by Gay Canvasser,7,4
1,Recycling Script by Gay Canvasser,5,2
1,Recycling Script by Gay Canvasser,1,2
1,Recycling Script by Gay Canvasser,3,2
1,Recycling Script by Gay Canvasser,2,3
1,Recycling Script by Gay Canvasser,4,3
1,Recycling Script by Gay Canvasser,6,3
1,No Contact,1,4
1,No Contact,4,4
1,No Contact,6,4
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,5,4
1,No Contact,7,4
1,No Contact,2,5
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,6,4
1,Recycling Script by Straight Canvasser,2,4
1,Recycling Script by Straight Canvasser,5,5
1,Recycling Script by Straight Canvasser,6,4
1,Recycling Script by Straight Canvasser,4,4
1,Recycling Script by Straight Canvasser,3,4
1,Recycling Script by Straight Canvasser,1,4
1,No Contact,5,2
1,No Contact,2,1
1,No Contact,7,3
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,3,1
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,1,1
2,Same-Sex Marriage Script by Gay Canvasser,2,2
2,Same-Sex Marriage Script by Gay Canvasser,3,2
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,No Contact,1,4
2,No Contact,4,3
2,No Contact,7,3
2,No Contact,2,4
2,No Contact,3,5
2,No Contact,1,1
2,No Contact,4,1
2,No Contact,2,2
2,No Contact,3,5
2,No Contact,7,5
2,No Contact,2,5
2,No Contact,1,5
2,No Contact,4,5
1,Same-Sex Marriage Script by Straight Canvasser,2,3
1,Same-Sex Marriage Script by Straight Canvasser,3,3
1,Same-Sex Marriage Script by Straight Canvasser,6,3
1,Same-Sex Marriage Script by Straight Canvasser,4,3
1,Same-Sex Marriage Script by Straight Canvasser,1,3
1,No Contact,1,1
1,No Contact,5,3
1,No Contact,2,1
1,No Contact,6,1
1,No Contact,4,1
1,No Contact,7,4
1,No Contact,7,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,4,4
1,No Contact,2,4
1,No Contact,3,5
1,No Contact,1,5
2,No Contact,3,1
2,No Contact,4,1
2,No Contact,2,1
2,No Contact,1,1
1,Recycling Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,7,2
1,Recycling Script by Gay Canvasser,2,1
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,4,1
1,Recycling Script by Gay Canvasser,5,1
1,Recycling Script by Gay Canvasser,4,2
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,2,1
1,Recycling Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,3,1
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,5,1
1,No Contact,7,1
1,No Contact,4,1
1,No Contact,3,1
1,No Contact,2,1
1,No Contact,7,1
1,No Contact,2,2
1,No Contact,5,2
1,No Contact,4,2
1,No Contact,6,2
1,No Contact,3,2
1,No Contact,1,2
1,No Contact,5,3
1,No Contact,6,1
1,No Contact,4,2
1,No Contact,1,1
1,No Contact,3,2
1,No Contact,2,2
1,No Contact,7,2
1,No Contact,2,5
1,No Contact,4,5
1,No Contact,7,5
1,No Contact,6,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,1,5
1,No Contact,5,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,2,4
1,No Contact,7,5
1,No Contact,4,4
1,No Contact,6,4
1,No Contact,1,4
1,No Contact,5,2
1,No Contact,3,4
1,Same-Sex Marriage Script by Gay Canvasser,7,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Recycling Script by Straight Canvasser,2,5
1,Recycling Script by Straight Canvasser,5,5
1,Recycling Script by Straight Canvasser,3,5
1,Recycling Script by Straight Canvasser,4,5
1,Recycling Script by Straight Canvasser,1,5
1,Recycling Script by Straight Canvasser,6,5
1,Recycling Script by Straight Canvasser,6,2
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,1,2
1,Recycling Script by Straight Canvasser,2,2
1,Recycling Script by Straight Canvasser,7,3
1,Recycling Script by Straight Canvasser,5,2
1,Recycling Script by Straight Canvasser,4,2
2,Same-Sex Marriage Script by Gay Canvasser,2,4
2,Same-Sex Marriage Script by Gay Canvasser,7,3
2,Same-Sex Marriage Script by Gay Canvasser,4,3
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,3,4
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,7,4
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,2,5
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,4,5
1,Recycling Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,4,4
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,7,4
2,Same-Sex Marriage Script by Gay Canvasser,1,4
2,Same-Sex Marriage Script by Gay Canvasser,2,2
1,No Contact,3,1
1,No Contact,5,2
1,No Contact,1,1
1,No Contact,2,1
1,No Contact,6,1
1,No Contact,6,4
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,4,5
1,No Contact,1,5
1,No Contact,6,4
1,No Contact,7,5
1,No Contact,2,5
1,Recycling Script by Straight Canvasser,2,4
1,Recycling Script by Straight Canvasser,4,4
1,Recycling Script by Straight Canvasser,1,4
2,No Contact,1,2
2,No Contact,3,1
2,No Contact,2,2
2,No Contact,4,2
2,Same-Sex Marriage Script by Gay Canvasser,7,5
2,Same-Sex Marriage Script by Gay Canvasser,4,5
2,Same-Sex Marriage Script by Gay Canvasser,1,5
2,Same-Sex Marriage Script by Gay Canvasser,3,5
2,Same-Sex Marriage Script by Gay Canvasser,2,5
2,Same-Sex Marriage Script by Gay Canvasser,2,3
2,Same-Sex Marriage Script by Gay Canvasser,1,3
2,Same-Sex Marriage Script by Gay Canvasser,4,3
2,Same-Sex Marriage Script by Gay Canvasser,7,2
1,No Contact,7,1
1,No Contact,6,2
1,No Contact,1,2
1,No Contact,2,2
1,No Contact,5,2
1,No Contact,4,2
1,No Contact,3,3
1,No Contact,6,1
1,No Contact,5,2
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,2,2
1,No Contact,1,1
1,No Contact,7,1
1,No Contact,2,5
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,4,1
1,No Contact,6,3
1,No Contact,5,4
1,No Contact,1,2
1,No Contact,2,2
1,No Contact,7,3
1,No Contact,2,3
1,No Contact,3,3
1,No Contact,6,2
1,No Contact,4,2
1,No Contact,1,2
1,No Contact,5,1
1,No Contact,1,2
1,No Contact,2,2
1,No Contact,3,2
1,No Contact,5,3
1,No Contact,4,2
1,No Contact,2,1
1,No Contact,6,1
1,No Contact,4,2
1,No Contact,5,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,4,3
1,No Contact,5,5
1,No Contact,7,4
1,No Contact,6,4
1,No Contact,3,3
1,No Contact,1,4
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,2,1
1,No Contact,7,1
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,2,1
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,5,2
1,No Contact,6,1
1,No Contact,2,3
1,No Contact,4,5
1,No Contact,1,4
1,No Contact,3,4
1,No Contact,5,3
1,No Contact,6,4
1,No Contact,7,5
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,2,1
1,No Contact,7,1
1,No Contact,2,2
1,No Contact,4,3
1,No Contact,6,3
1,No Contact,1,3
1,No Contact,7,3
1,No Contact,3,1
1,No Contact,5,4
1,No Contact,7,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,3,1
1,No Contact,2,1
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,7,5
1,No Contact,2,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,1,4
1,No Contact,6,4
1,No Contact,7,5
1,No Contact,3,4
1,No Contact,2,2
1,No Contact,4,4
1,No Contact,5,2
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,2,4
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,2,4
1,No Contact,6,5
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,5,4
1,No Contact,4,5
2,Same-Sex Marriage Script by Gay Canvasser,4,2
2,Same-Sex Marriage Script by Gay Canvasser,3,1
2,Same-Sex Marriage Script by Gay Canvasser,2,1
2,Same-Sex Marriage Script by Gay Canvasser,7,1
2,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,5,5
1,Recycling Script by Gay Canvasser,2,5
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,4,5
1,No Contact,2,4
1,No Contact,4,5
1,No Contact,1,4
1,No Contact,6,4
1,No Contact,5,4
1,No Contact,3,4
1,No Contact,4,4
1,No Contact,2,4
1,No Contact,7,3
1,No Contact,6,4
1,No Contact,3,4
1,No Contact,1,4
1,No Contact,5,5
1,No Contact,1,5
1,No Contact,3,5
1,No Contact,2,5
1,No Contact,7,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,4,5
1,Recycling Script by Gay Canvasser,1,4
1,Recycling Script by Gay Canvasser,6,4
1,Recycling Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,2,4
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,5,4
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,1,4
1,Recycling Script by Gay Canvasser,2,4
1,Recycling Script by Gay Canvasser,3,4
1,Same-Sex Marriage Script by Gay Canvasser,6,3
1,Same-Sex Marriage Script by Gay Canvasser,1,3
1,Same-Sex Marriage Script by Gay Canvasser,4,3
1,Same-Sex Marriage Script by Gay Canvasser,3,3
1,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Same-Sex Marriage Script by Gay Canvasser,5,1
1,Same-Sex Marriage Script by Gay Canvasser,3,1
1,Same-Sex Marriage Script by Gay Canvasser,4,1
1,Same-Sex Marriage Script by Gay Canvasser,2,1
1,Same-Sex Marriage Script by Gay Canvasser,6,1
1,Same-Sex Marriage Script by Gay Canvasser,7,1
1,Recycling Script by Straight Canvasser,1,3
1,Recycling Script by Straight Canvasser,6,3
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Straight Canvasser,3,3
1,Recycling Script by Straight Canvasser,2,4
1,Recycling Script by Straight Canvasser,7,4
1,Recycling Script by Straight Canvasser,3,2
1,Recycling Script by Straight Canvasser,2,3
1,Recycling Script by Straight Canvasser,4,2
1,Recycling Script by Straight Canvasser,6,2
1,Recycling Script by Straight Canvasser,1,2
1,Recycling Script by Straight Canvasser,5,2
1,No Contact,6,1
1,No Contact,3,2
1,No Contact,7,1
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,3,4
1,No Contact,4,4
1,No Contact,5,5
1,No Contact,7,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,4,5
1,No Contact,6,4
1,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Same-Sex Marriage Script by Gay Canvasser,4,1
1,Same-Sex Marriage Script by Gay Canvasser,6,1
1,Same-Sex Marriage Script by Gay Canvasser,2,1
1,Same-Sex Marriage Script by Gay Canvasser,7,1
1,Same-Sex Marriage Script by Gay Canvasser,1,2
1,Same-Sex Marriage Script by Gay Canvasser,6,2
1,Same-Sex Marriage Script by Gay Canvasser,3,2
1,Same-Sex Marriage Script by Gay Canvasser,5,2
1,Same-Sex Marriage Script by Gay Canvasser,4,2
1,Same-Sex Marriage Script by Gay Canvasser,2,2
1,Same-Sex Marriage Script by Gay Canvasser,7,4
1,Same-Sex Marriage Script by Gay Canvasser,3,3
1,Same-Sex Marriage Script by Gay Canvasser,6,3
1,Same-Sex Marriage Script by Gay Canvasser,4,3
1,Same-Sex Marriage Script by Gay Canvasser,1,3
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,No Contact,3,1
1,No Contact,4,1
1,No Contact,2,1
1,No Contact,5,1
1,No Contact,1,1
1,No Contact,6,1
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,2,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,1,5
1,No Contact,6,4
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,2,4
1,No Contact,7,5
1,No Contact,3,5
1,No Contact,3,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,2,5
1,No Contact,7,5
1,Recycling Script by Gay Canvasser,5,3
1,Recycling Script by Gay Canvasser,1,2
1,Recycling Script by Gay Canvasser,6,2
1,Recycling Script by Gay Canvasser,2,2
1,Recycling Script by Gay Canvasser,3,2
1,Recycling Script by Gay Canvasser,4,2
1,Recycling Script by Gay Canvasser,4,1
1,Recycling Script by Gay Canvasser,7,3
1,Recycling Script by Gay Canvasser,2,1
1,Recycling Script by Gay Canvasser,6,1
1,Recycling Script by Gay Canvasser,5,3
1,Recycling Script by Gay Canvasser,3,1
1,Recycling Script by Gay Canvasser,1,1
1,No Contact,6,4
1,No Contact,5,5
1,No Contact,1,4
1,No Contact,4,5
1,No Contact,7,4
1,No Contact,2,1
1,No Contact,5,1
1,No Contact,3,1
1,No Contact,6,1
1,No Contact,7,1
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,3,3
1,No Contact,2,4
1,No Contact,4,3
1,No Contact,7,2
1,No Contact,6,3
1,No Contact,5,2
1,No Contact,1,3
1,Recycling Script by Gay Canvasser,2,4
1,Recycling Script by Gay Canvasser,3,5
1,Recycling Script by Gay Canvasser,1,5
1,Recycling Script by Gay Canvasser,7,5
1,Recycling Script by Gay Canvasser,5,4
1,Recycling Script by Gay Canvasser,6,5
1,Recycling Script by Gay Canvasser,4,5
1,Recycling Script by Gay Canvasser,4,4
1,Recycling Script by Gay Canvasser,3,4
1,Recycling Script by Gay Canvasser,6,4
1,Recycling Script by Gay Canvasser,2,4
1,Recycling Script by Gay Canvasser,7,4
1,Recycling Script by Gay Canvasser,1,4
1,No Contact,1,2
1,No Contact,4,3
1,No Contact,5,3
1,No Contact,3,2
1,No Contact,6,2
1,No Contact,2,2
1,No Contact,1,4
1,No Contact,6,4
1,No Contact,4,4
1,No Contact,2,4
1,No Contact,7,4
1,No Contact,3,4
1,No Contact,5,3
1,No Contact,1,3
1,No Contact,3,4
1,No Contact,2,3
1,No Contact,5,4
1,No Contact,6,3
1,No Contact,4,3
1,Same-Sex Marriage Script by Gay Canvasser,7,1
1,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Same-Sex Marriage Script by Gay Canvasser,2,1
1,Same-Sex Marriage Script by Gay Canvasser,4,1
1,Same-Sex Marriage Script by Gay Canvasser,6,1
1,No Contact,5,2
1,No Contact,4,1
1,No Contact,2,2
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,3,1
1,No Contact,5,1
1,No Contact,6,1
1,No Contact,1,1
1,No Contact,4,1
1,No Contact,7,2
1,No Contact,4,4
1,No Contact,2,4
1,No Contact,5,4
1,No Contact,6,4
1,No Contact,1,4
1,No Contact,3,4
1,Same-Sex Marriage Script by Gay Canvasser,7,2
1,Same-Sex Marriage Script by Gay Canvasser,6,3
1,Same-Sex Marriage Script by Gay Canvasser,2,3
1,Same-Sex Marriage Script by Gay Canvasser,5,3
1,Same-Sex Marriage Script by Gay Canvasser,1,3
1,Same-Sex Marriage Script by Gay Canvasser,3,4
1,Same-Sex Marriage Script by Gay Canvasser,1,4
1,Same-Sex Marriage Script by Gay Canvasser,2,4
1,Same-Sex Marriage Script by Gay Canvasser,4,4
1,Same-Sex Marriage Script by Gay Canvasser,6,4
1,No Contact,2,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,3,5
1,No Contact,6,5
1,No Contact,4,5
1,No Contact,7,5
1,No Contact,6,5
1,No Contact,2,4
1,No Contact,1,5
1,Same-Sex Marriage Script by Straight Canvasser,3,1
1,Same-Sex Marriage Script by Straight Canvasser,1,1
1,Same-Sex Marriage Script by Straight Canvasser,5,1
1,Same-Sex Marriage Script by Straight Canvasser,4,1
1,Same-Sex Marriage Script by Straight Canvasser,6,5
1,Same-Sex Marriage Script by Straight Canvasser,2,5
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,Same-Sex Marriage Script by Straight Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,3,5
1,Same-Sex Marriage Script by Straight Canvasser,3,4
1,Same-Sex Marriage Script by Straight Canvasser,5,5
1,Same-Sex Marriage Script by Straight Canvasser,4,4
1,Same-Sex Marriage Script by Straight Canvasser,6,4
1,Same-Sex Marriage Script by Straight Canvasser,2,4
1,Same-Sex Marriage Script by Straight Canvasser,1,4
1,Same-Sex Marriage Script by Straight Canvasser,4,5
1,Same-Sex Marriage Script by Straight Canvasser,2,5
1,Same-Sex Marriage Script by Straight Canvasser,5,5
1,Same-Sex Marriage Script by Straight Canvasser,7,5
1,Same-Sex Marriage Script by Straight Canvasser,6,5
1,Same-Sex Marriage Script by Straight Canvasser,1,5
1,No Contact,1,5
1,No Contact,4,5
1,No Contact,5,5
1,No Contact,6,5
1,No Contact,2,5
1,No Contact,6,1
1,No Contact,4,1
1,No Contact,1,1
1,No Contact,3,1
1,No Contact,5,2
1,No Contact,2,1
1,No Contact,1,1
1,No Contact,7,1
1,No Contact,4,2
1,No Contact,6,1
1,No Contact,3,2
1,No Contact,2,1
1,No Contact,4,2
1,No Contact,3,2
1,No Contact,2,2
1,No Contact,5,3
1,No Contact,6,2
1,No Contact,1,2
1,No Contact,5,4
1,No Contact,7,5
1,No Contact,1,5
1,No Contact,2,5
1,No Contact,6,5
1,No Contact,6,2
1,No Contact,7,2
1,No Contact,4,2
1,No Contact,5,3
1,No Contact,3,2
1,No Contact,1,2
1,No Contact,2,2
1,Same-Sex Marriage Script by Gay Canvasser,6,5
1,Same-Sex Marriage Script by Gay Canvasser,3,5
1,Same-Sex Marriage Script by Gay Canvasser,5,5
1,Same-Sex Marriage Script by Gay Canvasser,2,5
1,Same-Sex Marriage Script by Gay Canvasser,1,5
1,Same-Sex Marriage Script by Gay Canvasser,4,5
1,Recycling Script by Straight Canvasser,3,5
1,Recycling Script by Straight Canvasser,6,5
1,Recycling Script by Straight Canvasser,4,5
1,Recycling Script by Straight Canvasser,1,5
1,Recycling Script by Straight Canvasser,2,5
1,Recycling Script by Straight Canvasser,5,4
1,Recycling Script by Straight Canvasser,7,5
1,No Contact,3,4
1,No Contact,4,5
1,No Contact,6,5
1,No Contact,1,5
1,No Contact,2,5
1,Recycling Script by Straight Canvasser,5,5
1,Recycling Script by Straight Canvasser,1,5
1,Recycling Script by Straight Canvasser,4,5
1,Recycling Script by Straight Canvasser,3,5
1,Recycling Script by Straight Canvasser,6,5
1,Recycling Script by Straight Canvasser,2,5
1,Recycling Script by Straight Canvasser,7,4
1,Same-Sex Marriage Script by Gay Canvasser,2,3
1,Same-Sex Marriage Script by Gay Canvasser,6,4
1,Same-Sex Marriage Script by Gay Canvasser,7,4
1,Same-Sex Marriage Script by Gay Canvasser,3,4
1,Same-Sex Marriage Script by Gay Canvasser,1,4
1,Same-Sex Marriage Script by Gay Canvasser,1,1
1,Same-Sex Marriage Script by Gay Canvasser,2,1
1,Same-Sex Marriage Script by Gay Canvasser,3,1
1,Same-Sex Marriage Script by Gay Can
gitextract__a6ivn47/ ├── .Rbuildignore ├── .gitignore ├── .travis.yml ├── CAUSALITY/ │ ├── README.md │ ├── STAR.csv │ ├── causality-tidy.R │ ├── causality-tidy.Rmd │ ├── causality.R │ ├── causality.Rmd │ ├── gay.csv │ ├── leaders.csv │ ├── minwage.csv │ ├── resume.csv │ └── social.csv ├── DESCRIPTION ├── DISCOVERY/ │ ├── README.md │ ├── constitution.csv │ ├── discovery-tidy.R │ ├── discovery-tidy.Rmd │ ├── discovery.R │ ├── discovery.Rmd │ ├── elections.csv │ ├── federalist/ │ │ ├── fp01.txt │ │ ├── fp02.txt │ │ ├── fp03.txt │ │ ├── fp04.txt │ │ ├── fp05.txt │ │ ├── fp06.txt │ │ ├── fp07.txt │ │ ├── fp08.txt │ │ ├── fp09.txt │ │ ├── fp10.txt │ │ ├── fp11.txt │ │ ├── fp12.txt │ │ ├── fp13.txt │ │ ├── fp14.txt │ │ ├── fp15.txt │ │ ├── fp16.txt │ │ ├── fp17.txt │ │ ├── fp18.txt │ │ ├── fp19.txt │ │ ├── fp20.txt │ │ ├── fp21.txt │ │ ├── fp22.txt │ │ ├── fp23.txt │ │ ├── fp24.txt │ │ ├── fp25.txt │ │ ├── fp26.txt │ │ ├── fp27.txt │ │ ├── fp28.txt │ │ ├── fp29.txt │ │ ├── fp30.txt │ │ ├── fp31.txt │ │ ├── fp32.txt │ │ ├── fp33.txt │ │ ├── fp34.txt │ │ ├── fp35.txt │ │ ├── fp36.txt │ │ ├── fp37.txt │ │ ├── fp38.txt │ │ ├── fp39.txt │ │ ├── fp40.txt │ │ ├── fp41.txt │ │ ├── fp42.txt │ │ ├── fp43.txt │ │ ├── fp44.txt │ │ ├── fp45.txt │ │ ├── fp46.txt │ │ ├── fp47.txt │ │ ├── fp48.txt │ │ ├── fp49.txt │ │ ├── fp50.txt │ │ ├── fp51.txt │ │ ├── fp52.txt │ │ ├── fp53.txt │ │ ├── fp54.txt │ │ ├── fp55.txt │ │ ├── fp56.txt │ │ ├── fp57.txt │ │ ├── fp58.txt │ │ ├── fp59.txt │ │ ├── fp60.txt │ │ ├── fp61.txt │ │ ├── fp62.txt │ │ ├── fp63.txt │ │ ├── fp64.txt │ │ ├── fp65.txt │ │ ├── fp66.txt │ │ ├── fp67.txt │ │ ├── fp68.txt │ │ ├── fp69.txt │ │ ├── fp70.txt │ │ ├── fp71.txt │ │ ├── fp72.txt │ │ ├── fp73.txt │ │ ├── fp74.txt │ │ ├── fp75.txt │ │ ├── fp76.txt │ │ ├── fp77.txt │ │ ├── fp78.txt │ │ ├── fp79.txt │ │ ├── fp80.txt │ │ ├── fp81.txt │ │ ├── fp82.txt │ │ ├── fp83.txt │ │ ├── fp84.txt │ │ └── fp85.txt │ ├── florentine.csv │ ├── pres08.csv │ ├── pres12.csv │ ├── trade.csv │ ├── twitter-following.csv │ ├── twitter-senator.csv │ └── walmart.csv ├── INTRO/ │ ├── Kenya.csv │ ├── README.md │ ├── Sweden.csv │ ├── UNpop-tidy.R │ ├── UNpop.R │ ├── UNpop.RData │ ├── UNpop.csv │ ├── UNpop.dta │ ├── World.csv │ ├── intro-tidy.R │ ├── intro-tidy.Rmd │ ├── intro.R │ ├── intro.Rmd │ └── turnout.csv ├── LICENSE ├── MEASUREMENT/ │ ├── README.md │ ├── USGini.csv │ ├── afghan-village.csv │ ├── afghan.csv │ ├── ccap2012.csv │ ├── congress.csv │ ├── gayreshaped.csv │ ├── measurement-tidy.R │ ├── measurement-tidy.Rmd │ ├── measurement.R │ ├── measurement.Rmd │ ├── unvoting.csv │ └── vignettes.csv ├── PREDICTION/ │ ├── MPs.csv │ ├── README.md │ ├── face.csv │ ├── florida.csv │ ├── intrade08.csv │ ├── intrade12.csv │ ├── polls08.csv │ ├── polls12.csv │ ├── pollsUS08.csv │ ├── prediction-tidy.R │ ├── prediction-tidy.Rmd │ ├── prediction.R │ ├── prediction.Rmd │ ├── pres08.csv │ ├── pres12.csv │ ├── progresa.csv │ ├── social.csv │ ├── transfer.csv │ └── women.csv ├── PROBABILITY/ │ ├── FLCensusVTD.csv │ ├── FLVoters.csv │ ├── README.md │ ├── fraud.RData │ ├── intrade08.csv │ ├── names.csv │ ├── pres08.csv │ ├── probability-tidy.R │ ├── probability-tidy.Rmd │ ├── probability.R │ └── probability.Rmd ├── README.md ├── UNCERTAINTY/ │ ├── MPs.csv │ ├── README.md │ ├── STAR.csv │ ├── chinawomen.csv │ ├── filedrawer.csv │ ├── minwage.csv │ ├── nazis.csv │ ├── polls08.csv │ ├── pres08.csv │ ├── published.csv │ ├── resume.csv │ ├── uncertainty-tidy.R │ ├── uncertainty-tidy.Rmd │ ├── uncertainty.R │ ├── uncertainty.Rmd │ └── women.csv ├── errata/ │ ├── QSS_tidyverse_errata.Rmd │ └── QSSerrata.Rmd ├── syllabus/ │ ├── README.md │ ├── RcampPrinceton.tex │ ├── calendar.sty │ ├── pol245Princeton.tex │ └── pol345soc305Princeton.tex └── test.R
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{
"path": ".gitignore",
"chars": 128,
"preview": "# History files\n.Rhistory\n.Rapp.history\n\n# Example code in package build process\n*-Ex.R\n\n# RStudio files\n.Rproj.user/\n.D"
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"path": ".travis.yml",
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"preview": "language: r\nwarnings_are_errors: true\nsudo: false\n\nscript:\n - Rscript test.R\n \nenv:\n global: \n - CRAN: http://cra"
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"path": "CAUSALITY/README.md",
"chars": 798,
"preview": "# Chapter 2: Causality\n\n## Code\n1. The markdown file for the entire chapter: [causality.Rmd](causality.Rmd) or [causalit"
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"preview": "## ---- message=FALSE---------------------------------------\n## Load required packages\nlibrary(tidyverse)\nlibrary(qss)\n\n"
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"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 2: Causality'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Print"
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"path": "CAUSALITY/leaders.csv",
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"preview": "\"year\",\"country\",\"leadername\",\"age\",\"politybefore\",\"polityafter\",\"interwarbefore\",\"interwarafter\",\"civilwarbefore\",\"civi"
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"preview": "\"chain\",\"location\",\"wageBefore\",\"wageAfter\",\"fullBefore\",\"fullAfter\",\"partBefore\",\"partAfter\"\n\"wendys\",\"PA\",5,5.25,20,0,"
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"preview": "\"firstname\",\"sex\",\"race\",\"call\"\n\"Allison\",\"female\",\"white\",0\n\"Kristen\",\"female\",\"white\",0\n\"Lakisha\",\"female\",\"black\",0\n\""
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"path": "CAUSALITY/social.csv",
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"preview": "\"sex\",\"yearofbirth\",\"primary2004\",\"messages\",\"primary2006\",\"hhsize\"\n\"male\",1941,0,\"Civic Duty\",0,2\n\"female\",1947,0,\"Civi"
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"preview": "## ---- message=FALSE, warning=FALSE------------------------\n## load the packages\nlibrary(\"tm\")\nlibrary(\"SnowballC\")\nlib"
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"preview": "\"year\",\"state\",\"county\",\"rep\",\"dem\",\"other\"\r\n1960,\"alabama\",\"autauga\",1149,1324,89\r\n1960,\"alabama\",\"baldwin\",4812,5647,1"
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"preview": "AFTER an unequivocal experience of the inefficiency of the subsisting \n federal government, you are called upon t"
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"path": "DISCOVERY/federalist/fp02.txt",
"chars": 11170,
"preview": "WHEN the people of America reflect that they are now called upon to decide \n a question, which, in its consequenc"
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{
"path": "DISCOVERY/federalist/fp03.txt",
"chars": 9623,
"preview": "IT IS not a new observation that the people of any country (if, like \n the Americans, intelligent and wellinforme"
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{
"path": "DISCOVERY/federalist/fp04.txt",
"chars": 10740,
"preview": "MY LAST paper assigned several reasons why the safety of the people would \n be best secured by union against the "
},
{
"path": "DISCOVERY/federalist/fp05.txt",
"chars": 9116,
"preview": "QUEEN ANNE, in her letter of the 1st July, 1706, to the Scotch Parliament, \n makes some observations on the impor"
},
{
"path": "DISCOVERY/federalist/fp06.txt",
"chars": 13246,
"preview": "THE three last numbers of this paper have been dedicated to an enumeration \n of the dangers to which we should be"
},
{
"path": "DISCOVERY/federalist/fp07.txt",
"chars": 15382,
"preview": "IT IS sometimes asked, with an air of seeming triumph, what inducements \n could the States have, if disunited, to"
},
{
"path": "DISCOVERY/federalist/fp08.txt",
"chars": 13473,
"preview": "ASSUMING it therefore as an established truth that the several States, \n in case of disunion, or such combination"
},
{
"path": "DISCOVERY/federalist/fp09.txt",
"chars": 13320,
"preview": "A FIRM Union will be of the utmost moment to the peace and liberty of \n the States, as a barrier against domestic"
},
{
"path": "DISCOVERY/federalist/fp10.txt",
"chars": 19929,
"preview": "AMONG the numerous advantages promised by a well-constructed Union, none \n deserves to be more accurately develop"
},
{
"path": "DISCOVERY/federalist/fp11.txt",
"chars": 16662,
"preview": "THE importance of the Union, in a commercial light, is one of those points \n about which there is least room to e"
},
{
"path": "DISCOVERY/federalist/fp12.txt",
"chars": 14385,
"preview": "THE effects of Union upon the commercial prosperity of the States have \n been sufficiently delineated. Its tenden"
},
{
"path": "DISCOVERY/federalist/fp13.txt",
"chars": 6406,
"preview": "As CONNECTED with the subject of revenue, we may with propriety consider \n that of economy. The money saved from "
},
{
"path": "DISCOVERY/federalist/fp14.txt",
"chars": 14148,
"preview": "WE HAVE seen the necessity of the Union, as our bulwark against foreign \n danger, as the conservator of peace amo"
},
{
"path": "DISCOVERY/federalist/fp15.txt",
"chars": 20447,
"preview": "IN THE course of the preceding papers, I have endeavored, my fellow-citizens, \n to place before you, in a clear a"
},
{
"path": "DISCOVERY/federalist/fp16.txt",
"chars": 13477,
"preview": "THE tendency of the principle of legislation for States, or communities, \n in their political capacities, as it h"
},
{
"path": "DISCOVERY/federalist/fp17.txt",
"chars": 10735,
"preview": "AN OBJECTION, of a nature different from that which has been stated and \n answered, in my last address, may perha"
},
{
"path": "DISCOVERY/federalist/fp18.txt",
"chars": 14319,
"preview": "AMONG the confederacies of antiquity, the most considerable was that \n of the Grecian republics, associated under"
},
{
"path": "DISCOVERY/federalist/fp19.txt",
"chars": 13929,
"preview": "THE examples of ancient confederacies, cited in my last paper, have not \n exhausted the source of experimental in"
},
{
"path": "DISCOVERY/federalist/fp20.txt",
"chars": 10664,
"preview": "THE United Netherlands are a confederacy of republics, or rather of aristocracies \n of a very remarkable texture,"
},
{
"path": "DISCOVERY/federalist/fp21.txt",
"chars": 13293,
"preview": "HAVING in the three last numbers taken a summary review of the principal \n circumstances and events which have de"
},
{
"path": "DISCOVERY/federalist/fp22.txt",
"chars": 23145,
"preview": "IN ADDITION to the defects already enumerated in the existing federal \n system, there are others of not less impo"
},
{
"path": "DISCOVERY/federalist/fp23.txt",
"chars": 11972,
"preview": "THE necessity of a Constitution, at least equally energetic with the \n one proposed, to the preservation of the U"
},
{
"path": "DISCOVERY/federalist/fp24.txt",
"chars": 12067,
"preview": "To THE powers proposed to be conferred upon the federal government, in \n respect to the creation and direction of"
},
{
"path": "DISCOVERY/federalist/fp25.txt",
"chars": 12996,
"preview": "IT MAY perhaps be urged that the objects enumerated in the preceding \n number ought to be provided for by the Sta"
},
{
"path": "DISCOVERY/federalist/fp26.txt",
"chars": 15466,
"preview": "IT WAS a thing hardly to be expected that in a popular revolution the \n minds of men should stop at that happy me"
},
{
"path": "DISCOVERY/federalist/fp27.txt",
"chars": 9435,
"preview": "IT HAS been urged, in different shapes, that a Constitution of the kind \n proposed by the convention cannot opera"
},
{
"path": "DISCOVERY/federalist/fp28.txt",
"chars": 10627,
"preview": "THAT there may happen cases in which the national government may be necessitated \n to resort to force, cannot be "
},
{
"path": "DISCOVERY/federalist/fp29.txt",
"chars": 14462,
"preview": "THE power of regulating the militia, and of commanding its services in \n times of insurrection and invasion are n"
},
{
"path": "DISCOVERY/federalist/fp30.txt",
"chars": 13019,
"preview": "IT HAS been already observed that the federal government ought to possess \n the power of providing for the suppor"
},
{
"path": "DISCOVERY/federalist/fp31.txt",
"chars": 11387,
"preview": "IN DISQUISITIONS of every kind, there are certain primary truths, or \n first principles, upon which all subsequen"
},
{
"path": "DISCOVERY/federalist/fp32.txt",
"chars": 9869,
"preview": "ALTHOUGH I am of opinion that there would be no real danger of the consequences \n which seem to be apprehended to"
},
{
"path": "DISCOVERY/federalist/fp33.txt",
"chars": 10962,
"preview": "THE residue of the argument against the provisions of the Constitution \n in respect to taxation is ingrafted upon"
},
{
"path": "DISCOVERY/federalist/fp34.txt",
"chars": 14437,
"preview": "I FLATTER myself it has been clearly shown in my last number that the \n particular States, under the proposed Con"
},
{
"path": "DISCOVERY/federalist/fp35.txt",
"chars": 14881,
"preview": "BEFORE we proceed to examine any other objections to an indefinite power \n of taxation in the Union, I shall make"
},
{
"path": "DISCOVERY/federalist/fp36.txt",
"chars": 17793,
"preview": "WE HAVE seen that the result of the observations, to which the foregoing \n number has been principally devoted, i"
},
{
"path": "DISCOVERY/federalist/fp37.txt",
"chars": 18565,
"preview": "IN REVIEWING the defects of the existing Confederation, and showing that \n they cannot be supplied by a governmen"
},
{
"path": "DISCOVERY/federalist/fp38.txt",
"chars": 21841,
"preview": "IT IS not a little remarkable that in every case reported by ancient \n history, in which government has been esta"
},
{
"path": "DISCOVERY/federalist/fp39.txt",
"chars": 17343,
"preview": "THE last paper having concluded the observations which were meant to \n introduce a candid survey of the plan of g"
},
{
"path": "DISCOVERY/federalist/fp40.txt",
"chars": 20448,
"preview": "THE SECOND point to be examined is, whether the convention were authorized \n to frame and propose this mixed Cons"
},
{
"path": "DISCOVERY/federalist/fp41.txt",
"chars": 23575,
"preview": "THE Constitution proposed by the convention may be considered under two \n general points of view. The FIRST relat"
},
{
"path": "DISCOVERY/federalist/fp42.txt",
"chars": 18877,
"preview": "THE SECOND class of powers, lodged in the general government, consists \n of those which regulate the intercourse "
},
{
"path": "DISCOVERY/federalist/fp43.txt",
"chars": 23150,
"preview": "THE FOURTH class comprises the following miscellaneous powers:1. A power \n \"to promote the progress of science an"
},
{
"path": "DISCOVERY/federalist/fp44.txt",
"chars": 19509,
"preview": "A FIFTH class of provisions in favor of the federal authority consists \n of the following restrictions on the aut"
},
{
"path": "DISCOVERY/federalist/fp45.txt",
"chars": 14401,
"preview": "HAVING shown that no one of the powers transferred to the federal government \n is unnecessary or improper, the ne"
},
{
"path": "DISCOVERY/federalist/fp46.txt",
"chars": 17617,
"preview": "RESUMING the subject of the last paper, I proceed to inquire whether \n the federal government or the State govern"
},
{
"path": "DISCOVERY/federalist/fp47.txt",
"chars": 18904,
"preview": "HAVING reviewed the general form of the proposed government and the general \n mass of power allotted to it, I pro"
},
{
"path": "DISCOVERY/federalist/fp48.txt",
"chars": 12837,
"preview": "IT WAS shown in the last paper that the political apothegm there examined \n does not require that the legislative"
},
{
"path": "DISCOVERY/federalist/fp49.txt",
"chars": 11067,
"preview": "THE author of the \"Notes on the State of Virginia,\" quoted in the last \n paper, has subjoined to that valuable wo"
},
{
"path": "DISCOVERY/federalist/fp50.txt",
"chars": 7606,
"preview": "IT MAY be contended, perhaps, that instead of OCCASIONAL appeals to the \n people, which are liable to the objecti"
},
{
"path": "DISCOVERY/federalist/fp51.txt",
"chars": 12957,
"preview": "TO WHAT expedient, then, shall we finally resort, for maintaining in \n practice the necessary partition of power "
},
{
"path": "DISCOVERY/federalist/fp52.txt",
"chars": 12325,
"preview": "FROM the more general inquiries pursued in the four last papers, I pass \n on to a more particular examination of "
},
{
"path": "DISCOVERY/federalist/fp53.txt",
"chars": 14554,
"preview": "I SHALL here, perhaps, be reminded of a current observation, \"that where \n annual elections end, tyranny begins. "
},
{
"path": "DISCOVERY/federalist/fp54.txt",
"chars": 13192,
"preview": "THE next view which I shall take of the House of Representatives relates \n to the appointment of its members to t"
},
{
"path": "DISCOVERY/federalist/fp55.txt",
"chars": 13437,
"preview": "THE number of which the House of Representatives is to consist, forms \n another and a very interesting point of v"
},
{
"path": "DISCOVERY/federalist/fp56.txt",
"chars": 10562,
"preview": "THE SECOND charge against the House of Representatives is, that it will \n be too small to possess a due knowledge"
},
{
"path": "DISCOVERY/federalist/fp57.txt",
"chars": 14505,
"preview": "THE THIRD charge against the House of Representatives is, that it will \n be taken from that class of citizens whi"
},
{
"path": "DISCOVERY/federalist/fp58.txt",
"chars": 14147,
"preview": "THE remaining charge against the House of Representatives, which I am \n to examine, is grounded on a supposition "
},
{
"path": "DISCOVERY/federalist/fp59.txt",
"chars": 12498,
"preview": "THE natural order of the subject leads us to consider, in this place, \n that provision of the Constitution which "
},
{
"path": "DISCOVERY/federalist/fp60.txt",
"chars": 14739,
"preview": "WE HAVE seen, that an uncontrollable power over the elections to the \n federal government could not, without haza"
},
{
"path": "DISCOVERY/federalist/fp61.txt",
"chars": 9812,
"preview": "THE more candid opposers of the provision respecting elections, contained \n in the plan of the convention, when p"
},
{
"path": "DISCOVERY/federalist/fp62.txt",
"chars": 15771,
"preview": "HAVING examined the constitution of the House of Representatives, and \n answered such of the objections against i"
},
{
"path": "DISCOVERY/federalist/fp63.txt",
"chars": 20338,
"preview": "A FIFTH desideratum, illustrating the utility of a senate, is the want \n of a due sense of national character. Wi"
},
{
"path": "DISCOVERY/federalist/fp64.txt",
"chars": 15066,
"preview": "IT IS a just and not a new observation, that enemies to particular persons, \n and opponents to particular measure"
},
{
"path": "DISCOVERY/federalist/fp65.txt",
"chars": 13221,
"preview": "THE remaining powers which the plan of the convention allots to the Senate, \n in a distinct capacity, are compris"
},
{
"path": "DISCOVERY/federalist/fp66.txt",
"chars": 14550,
"preview": "A REVIEW of the principal objections that have appeared against the proposed \n court for the trial of impeachment"
},
{
"path": "DISCOVERY/federalist/fp67.txt",
"chars": 10976,
"preview": "THE constitution of the executive department of the proposed government, \n claims next our attention. There is ha"
},
{
"path": "DISCOVERY/federalist/fp68.txt",
"chars": 9745,
"preview": "THE mode of appointment of the Chief Magistrate of the United States \n is almost the only part of the system, of "
},
{
"path": "DISCOVERY/federalist/fp69.txt",
"chars": 17939,
"preview": "I PROCEED now to trace the real characters of the proposed Executive, \n as they are marked out in the plan of the"
},
{
"path": "DISCOVERY/federalist/fp70.txt",
"chars": 20437,
"preview": "THERE is an idea, which is not without its advocates, that a vigorous \n Executive is inconsistent with the genius"
},
{
"path": "DISCOVERY/federalist/fp71.txt",
"chars": 11129,
"preview": "DURATION in office has been mentioned as the second requisite to the \n energy of the Executive authority. This ha"
},
{
"path": "DISCOVERY/federalist/fp72.txt",
"chars": 13386,
"preview": "THE administration of government, in its largest sense, comprehends all \n the operations of the body politic, whe"
},
{
"path": "DISCOVERY/federalist/fp73.txt",
"chars": 15268,
"preview": "THE third ingredient towards constituting the vigor of the executive \n authority, is an adequate provision for it"
},
{
"path": "DISCOVERY/federalist/fp74.txt",
"chars": 6539,
"preview": "THE President of the United States is to be \"commander-in-chief of the \n army and navy of the United States, and "
},
{
"path": "DISCOVERY/federalist/fp75.txt",
"chars": 12680,
"preview": "THE President is to have power, \"by and with the advice and consent of \n the Senate, to make treaties, provided t"
},
{
"path": "DISCOVERY/federalist/fp76.txt",
"chars": 12549,
"preview": "THE President is \"to NOMINATE, and, by and with the advice and consent \n of the Senate, to appoint ambassadors, o"
},
{
"path": "DISCOVERY/federalist/fp77.txt",
"chars": 12970,
"preview": "IT HAS been mentioned as one of the advantages to be expected from the \n co-operation of the Senate, in the busin"
},
{
"path": "DISCOVERY/federalist/fp78.txt",
"chars": 20046,
"preview": "WE PROCEED now to an examination of the judiciary department of the proposed \n government. In unfolding the defec"
},
{
"path": "DISCOVERY/federalist/fp79.txt",
"chars": 6697,
"preview": "NEXT to permanency in office, nothing can contribute more to the independence \n of the judges than a fixed provis"
},
{
"path": "DISCOVERY/federalist/fp80.txt",
"chars": 16408,
"preview": "To JUDGE with accuracy of the proper extent of the federal judicature, \n it will be necessary to consider, in the"
},
{
"path": "DISCOVERY/federalist/fp81.txt",
"chars": 24663,
"preview": "LET US now return to the partition of the judiciary authority between \n different courts, and their relations to "
},
{
"path": "DISCOVERY/federalist/fp82.txt",
"chars": 10159,
"preview": "THE erection of a new government, whatever care or wisdom may distinguish \n the work, cannot fail to originate qu"
},
{
"path": "DISCOVERY/federalist/fp83.txt",
"chars": 37198,
"preview": "THE objection to the plan of the convention, which has met with most \n success in this State, and perhaps in seve"
},
{
"path": "DISCOVERY/federalist/fp84.txt",
"chars": 25675,
"preview": "IN THE course of the foregoing review of the Constitution, I have taken \n notice of, and endeavored to answer mos"
},
{
"path": "DISCOVERY/federalist/fp85.txt",
"chars": 17472,
"preview": "ACCORDING to the formal division of the subject of these papers, announced \n in my first number, there would appe"
},
{
"path": "DISCOVERY/florentine.csv",
"chars": 855,
"preview": "\"FAMILY\",\"ACCIAIUOL\",\"ALBIZZI\",\"BARBADORI\",\"BISCHERI\",\"CASTELLAN\",\"GINORI\",\"GUADAGNI\",\"LAMBERTES\",\"MEDICI\",\"PAZZI\",\"PERU"
},
{
"path": "DISCOVERY/pres08.csv",
"chars": 1305,
"preview": "\"state.name\",\"state\",\"Obama\",\"McCain\",\"EV\"\n\"Alabama\",\"AL\",39,60,9\n\"Alaska\",\"AK\",38,59,3\n\"Arizona\",\"AZ\",45,54,10\n\"Arkansa"
},
{
"path": "DISCOVERY/pres12.csv",
"chars": 713,
"preview": "\"state\",\"Obama\",\"Romney\",\"EV\"\n\"AL\",38,61,9\n\"AK\",41,55,3\n\"AZ\",45,54,11\n\"AR\",37,61,6\n\"CA\",60,37,55\n\"CO\",51,46,9\n\"CT\",58,41"
},
{
"path": "DISCOVERY/trade.csv",
"chars": 4615366,
"preview": "\"\",\"country1\",\"country2\",\"year\",\"exports\"\n\"1\",\"United States of America\",\"Haiti\",1900,NA\n\"2\",\"United States of America\","
},
{
"path": "DISCOVERY/twitter-following.csv",
"chars": 118090,
"preview": "\"following\",\"followed\"\n\"SenAlexander\",\"RoyBlunt\"\n\"SenAlexander\",\"SenatorBurr\"\n\"SenAlexander\",\"JohnBoozman\"\n\"SenAlexander"
},
{
"path": "DISCOVERY/twitter-senator.csv",
"chars": 3715,
"preview": "\"screen_name\",\"name\",\"party\",\"state\"\n\"SenAlexander\",\"Lamar Alexander\",\"R\",\"TN\"\n\"RoyBlunt\",\"Roy Blunt\",\"R\",\"MO\"\n\"SenatorB"
},
{
"path": "DISCOVERY/walmart.csv",
"chars": 277279,
"preview": "\"opendate\",\"st.address\",\"city\",\"state\",\"long\",\"lat\",\"type\"\n1962-03-01,\"5801 SW Regional Airport Blvd\",\"Bentonville\",\"AR\""
},
{
"path": "INTRO/Kenya.csv",
"chars": 1872,
"preview": "country,period,age,births,deaths,py.men,py.women,l_x\rKEN,1950-1955,0-4,0,398.314,2982.589,2977.828,100000\rKEN,1950-1955,"
},
{
"path": "INTRO/README.md",
"chars": 776,
"preview": "# Chapter 1: Introduction\n\n## Code\n1. The markdown file for the entire chapter: [intro.Rmd](intro.Rmd) or [intro-tidy.Rm"
},
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"path": "INTRO/Sweden.csv",
"chars": 1831,
"preview": "country,period,age,births,deaths,py.men,py.women,l_x\rSWE,1950-1955,0-4,0,13.765,1490.037,1410.502,100000\rSWE,1950-1955,5"
},
{
"path": "INTRO/UNpop-tidy.R",
"chars": 490,
"preview": "##\n## File: UNpop.R\n## Author: Kosuke Imai and Nora Webb Williams\n## The code loads the UN population data, adds a varia"
},
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"path": "INTRO/UNpop.R",
"chars": 268,
"preview": "##\n## File: UNpop.R\n## Author: Kosuke Imai\n## The code loads the UN population data and saves it as a STATA file\n##\nlibr"
},
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"path": "INTRO/UNpop.csv",
"chars": 113,
"preview": "year, world.pop\n1950, 2525779\n1960, 3026003\n1970, 3691173\n1980, 4449049\n1990, 5320817\n2000, 6127700\n2010, 6916183"
},
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"path": "INTRO/World.csv",
"chars": 1821,
"preview": "country,period,age,births,deaths,py.men,py.women\rWORLD,1950-1955,0-4,0,101090.393,946910.589,904909.277\rWORLD,1950-1955,"
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"path": "INTRO/intro-tidy.R",
"chars": 11325,
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},
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"path": "INTRO/intro-tidy.Rmd",
"chars": 9345,
"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 1: Introduction'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Pr"
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{
"path": "INTRO/intro.R",
"chars": 3971,
"preview": "## ---- eval = FALSE-------------------------------------------------------\n## install.packages(\"swirl\") # install the p"
},
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"path": "INTRO/intro.Rmd",
"chars": 3781,
"preview": "---\ntitle: 'Code for QSS Chapter 1: Introduction'\nauthor: \"Kosuke Imai\"\ndate: \"First Printing\"\noutput:\n pdf_document: d"
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"path": "INTRO/turnout.csv",
"chars": 730,
"preview": "\"year\",\"VEP\",\"VAP\",\"total\",\"ANES\",\"felons\",\"noncit\",\"overseas\",\"osvoters\"\n1980,159635,164445,86515,71,802,5756,1803,NA\n1"
},
{
"path": "LICENSE",
"chars": 18047,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 2, June 1991\n\n Copyright (C) 1989, 1991 Fr"
},
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"path": "MEASUREMENT/README.md",
"chars": 1035,
"preview": "# Chapter 3: Measurement\n\n## Code\n1. The markdown file for the entire chapter: [measurement.Rmd](measurement.Rmd) or [me"
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"path": "MEASUREMENT/USGini.csv",
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},
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"path": "MEASUREMENT/afghan-village.csv",
"chars": 26021,
"preview": "\"altitude\",\"population\",\"village.surveyed\"\n1959.08,197,1\n2425.8799,744,0\n2236.6001,179,1\n1691.76,225,0\n1928.04,379,0\n119"
},
{
"path": "MEASUREMENT/afghan.csv",
"chars": 167667,
"preview": "\"province\",\"district\",\"village.id\",\"age\",\"educ.years\",\"employed\",\"income\",\"violent.exp.ISAF\",\"violent.exp.taliban\",\"list"
},
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"path": "MEASUREMENT/ccap2012.csv",
"chars": 644247,
"preview": "\"\",\"caseid\",\"gaytherm\"\n\"1\",328,50\n\"2\",324,95\n\"3\",100,16\n\"4\",584,50\n\"5\",63,58\n\"6\",461,100\n\"7\",81,93\n\"8\",735,NA\n\"9\",565,72"
},
{
"path": "MEASUREMENT/congress.csv",
"chars": 1087766,
"preview": "\"congress\",\"district\",\"state\",\"party\",\"name\",\"dwnom1\",\"dwnom2\"\n80,0,\"USA\",\"Democrat\",\"TRUMAN\",-0.275999993085861,0.01600"
},
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"path": "MEASUREMENT/gayreshaped.csv",
"chars": 487124,
"preview": "\"study\",\"treatment\",\"therm1\",\"therm2\",\"therm3\",\"therm4\"\n1,\"No Contact\",91,91,NA,NA\n1,\"No Contact\",72,72,NA,NA\n1,\"No Cont"
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"path": "MEASUREMENT/measurement-tidy.R",
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"path": "MEASUREMENT/measurement-tidy.Rmd",
"chars": 18892,
"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 3: Measurement'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Pri"
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"path": "MEASUREMENT/measurement.R",
"chars": 9952,
"preview": "## ------------------------------------------------------------------------\n## load data\nafghan <- read.csv(\"afghan.csv\""
},
{
"path": "MEASUREMENT/measurement.Rmd",
"chars": 9857,
"preview": "---\ntitle: 'Code for QSS Chapter 3: Measurement'\nauthor: \"Kosuke Imai\"\ndate: \"First Printing\"\noutput:\n pdf_document: de"
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"path": "MEASUREMENT/unvoting.csv",
"chars": 441263,
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},
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"path": "MEASUREMENT/vignettes.csv",
"chars": 10980,
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},
{
"path": "PREDICTION/MPs.csv",
"chars": 53125,
"preview": "\"surname\",\"firstname\",\"party\",\"ln.gross\",\"ln.net\",\"yob\",\"yod\",\"margin.pre\",\"region\",\"margin\"\n\"Llewellyn\",\"David\",\"tory\","
},
{
"path": "PREDICTION/README.md",
"chars": 1466,
"preview": "# Chapter 4: Prediction\n\n## Code\n1. The markdown file for the entire chapter: [prediction.Rmd](prediction.Rmd) or [predi"
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"path": "PREDICTION/face.csv",
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},
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"path": "PREDICTION/florida.csv",
"chars": 2677,
"preview": "county,Clinton96,Dole96,Perot96,Bush00,Gore00,Buchanan00\rAlachua,40144,25303,8072,34124,47365,263\rBaker,2273,3684,667,56"
},
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"chars": 1723483,
"preview": "\"\",\"day\",\"statename\",\"PriceD\",\"VolumeD\",\"PriceR\",\"VolumeR\",\"state\"\n\"1\",2006-11-12,\"Alabama\",40,0,40,0,\"AL\"\n\"2\",2006-11-1"
},
{
"path": "PREDICTION/intrade12.csv",
"chars": 1448215,
"preview": "\"\",\"day\",\"statename\",\"PriceD\",\"VolumeD\",\"PriceR\",\"VolumeR\",\"state\"\n\"1\",2011-01-24,\"Alabama\",0,0,0,0,\"AL\"\n\"2\",2011-01-24,"
},
{
"path": "PREDICTION/polls08.csv",
"chars": 50644,
"preview": "\"state\",\"Pollster\",\"Obama\",\"McCain\",\"middate\"\n\"AL\",\"SurveyUSA-2\",36,61,2008-10-27\n\"AL\",\"Capital Survey-2\",34,54,2008-10-"
},
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"path": "PREDICTION/polls12.csv",
"chars": 55871,
"preview": "\"\",\"state\",\"Obama\",\"Romney\",\"Pollster\",\"middate\"\n\"1\",\"AL\",36,51,\"Capital Survey Research Center\",2012-06-27\n\"2\",\"AZ\",46,"
},
{
"path": "PREDICTION/pollsUS08.csv",
"chars": 16805,
"preview": "\"Pollster\",\"McCain\",\"Obama\",\"middate\"\n\"IBD/TIPP \",48,36,2007-07-04\n\"GWU (Lake/Tarrance) \",51,39,2007-07-11\n\"Diageo/Hotli"
},
{
"path": "PREDICTION/prediction-tidy.R",
"chars": 28331,
"preview": "## ---- eval = FALSE----------------------------------------\n## for (i in X) {\n## expression1\n## expression2\n## "
},
{
"path": "PREDICTION/prediction-tidy.Rmd",
"chars": 24287,
"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 4: Prediction'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Prin"
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{
"path": "PREDICTION/prediction.R",
"chars": 17936,
"preview": "## ------------------------------------------------------------------------\nvalues <- c(2, 4, 6)\nn <- length(values) # n"
},
{
"path": "PREDICTION/prediction.Rmd",
"chars": 17985,
"preview": "---\ntitle: 'Code for QSS Chapter 4: Prediction'\nauthor: \"Kosuke Imai\"\ndate: \"Second Printing\"\noutput:\n pdf_document: de"
},
{
"path": "PREDICTION/pres08.csv",
"chars": 1305,
"preview": "\"state.name\",\"state\",\"Obama\",\"McCain\",\"EV\"\n\"Alabama\",\"AL\",39,60,9\n\"Alaska\",\"AK\",38,59,3\n\"Arizona\",\"AZ\",45,54,10\n\"Arkansa"
},
{
"path": "PREDICTION/pres12.csv",
"chars": 713,
"preview": "\"state\",\"Obama\",\"Romney\",\"EV\"\n\"AL\",38,61,9\n\"AK\",41,55,3\n\"AZ\",45,54,11\n\"AR\",37,61,6\n\"CA\",60,37,55\n\"CO\",51,46,9\n\"CT\",58,41"
},
{
"path": "PREDICTION/progresa.csv",
"chars": 93956,
"preview": "\"treatment\",\"pri2000s\",\"pri2000v\",\"t2000\",\"t2000r\",\"pri1994\",\"pan1994\",\"prd1994\",\"pri1994s\",\"pri1994v\",\"pan1994s\",\"pan19"
},
{
"path": "PREDICTION/social.csv",
"chars": 9137184,
"preview": "\"sex\",\"yearofbirth\",\"primary2004\",\"messages\",\"primary2006\",\"hhsize\"\n\"male\",1941,0,\"Civic Duty\",0,2\n\"female\",1947,0,\"Civi"
},
{
"path": "PREDICTION/transfer.csv",
"chars": 192379,
"preview": "\"\",\"state\",\"region\",\"literate91\",\"educ91\",\"poverty91\",\"poverty80\",\"educ80\",\"pop82\"\r\n\"55\",\"AC\",\"N\",0.727810621261597,3.87"
},
{
"path": "PREDICTION/women.csv",
"chars": 4533,
"preview": "\"GP\",\"village\",\"reserved\",\"female\",\"irrigation\",\"water\"\n1,2,1,1,0,10\n1,1,1,1,5,0\n2,2,1,1,2,2\n2,1,1,1,4,31\n3,2,0,0,0,0\n3,"
},
{
"path": "PROBABILITY/FLCensusVTD.csv",
"chars": 871267,
"preview": "\"county\",\"VTD\",\"total.pop\",\"white\",\"black\",\"hispanic\",\"api\",\"others\"\n1,46,4482,0.613788487282463,0.187193217313699,0.120"
},
{
"path": "PROBABILITY/FLVoters.csv",
"chars": 322800,
"preview": "\"surname\",\"county\",\"VTD\",\"age\",\"gender\",\"race\"\r\n\"PIEDRA\",115,66,58,\"f\",\"white\"\r\n\"LYNCH\",115,13,51,\"m\",\"white\"\r\n\"CHESTER\""
},
{
"path": "PROBABILITY/README.md",
"chars": 928,
"preview": "# Chapter 6: Probability\n\n## Code\n1. The markdown file for the entire chapter: [probability.Rmd](probability.Rmd) or [pr"
},
{
"path": "PROBABILITY/intrade08.csv",
"chars": 8146138,
"preview": "\"\",\"day\",\"statename\",\"MarketD\",\"PriceD\",\"VolumeD\",\"MarketR\",\"PriceR\",\"VolumeR\",\"state\"\n\"1\",2006-11-12,\"Alabama\",\"Democra"
},
{
"path": "PROBABILITY/names.csv",
"chars": 8419287,
"preview": "\"surname\",\"count\",\"pctwhite\",\"pctblack\",\"pctapi\",\"pcthispanic\",\"pctothers\"\n\"SMITH\",2376206,73.3426657334267,22.217778222"
},
{
"path": "PROBABILITY/pres08.csv",
"chars": 1305,
"preview": "\"state.name\",\"state\",\"Obama\",\"McCain\",\"EV\"\n\"Alabama\",\"AL\",39,60,9\n\"Alaska\",\"AK\",38,59,3\n\"Arizona\",\"AZ\",45,54,10\n\"Arkansa"
},
{
"path": "PROBABILITY/probability-tidy.R",
"chars": 28975,
"preview": "## ----message=FALSE, warning =FALSE------------------------\nlibrary(tidyverse)\n## write the birthday function\nbirthday "
},
{
"path": "PROBABILITY/probability-tidy.Rmd",
"chars": 23720,
"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 6: Probability'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Pri"
},
{
"path": "PROBABILITY/probability.R",
"chars": 15349,
"preview": "## -----------------------------------------------------------------------------\nbirthday <- function(k) {\n logdenom "
},
{
"path": "PROBABILITY/probability.Rmd",
"chars": 15296,
"preview": "---\ntitle: 'Code for QSS Chapter 6: Probability'\nauthor: \"Kosuke Imai\"\ndate: \"Third Printing\"\noutput:\n pdf_document: de"
},
{
"path": "README.md",
"chars": 3331,
"preview": "# QSS (Quantitative Social Science) [](https://tr"
},
{
"path": "UNCERTAINTY/MPs.csv",
"chars": 53125,
"preview": "\"surname\",\"firstname\",\"party\",\"ln.gross\",\"ln.net\",\"yob\",\"yod\",\"margin.pre\",\"region\",\"margin\"\n\"Llewellyn\",\"David\",\"tory\","
},
{
"path": "UNCERTAINTY/README.md",
"chars": 1291,
"preview": "# Chapter 7: Uncertainty\n\n## Code\n1. The markdown for the entire chapter: [uncertainty.Rmd](uncertainty.Rmd) or [uncerta"
},
{
"path": "UNCERTAINTY/STAR.csv",
"chars": 96641,
"preview": "\"race\",\"classtype\",\"yearssmall\",\"hsgrad\",\"g4math\",\"g4reading\"\n1,3,0,NA,NA,NA\n2,3,0,NA,706,661\n1,3,0,1,711,750\n2,1,4,NA,6"
},
{
"path": "UNCERTAINTY/chinawomen.csv",
"chars": 2618228,
"preview": "\"admin\",\"biryr\",\"birpop\",\"han\",\"sex\",\"teasown\",\"orch\",\"cashcrop\",\"post\"\n372301,1962,41,1,0.48780489,0,0.239999995,0.8400"
},
{
"path": "UNCERTAINTY/filedrawer.csv",
"chars": 8642,
"preview": "\"id\",\"journal\",\"DV\",\"IV\",\"max.h\"\n1,NA,\"Unwritten\",\"Null\",12\n2,\"COMMUNICATION\",\"Published, non top\",\"Weak\",9\n3,\"OTHER\",\"P"
},
{
"path": "UNCERTAINTY/minwage.csv",
"chars": 13974,
"preview": "\"chain\",\"location\",\"wageBefore\",\"wageAfter\",\"fullBefore\",\"fullAfter\",\"partBefore\",\"partAfter\"\n\"wendys\",\"PA\",5,5.25,20,0,"
},
{
"path": "UNCERTAINTY/nazis.csv",
"chars": 42553,
"preview": "\"shareself\",\"shareblue\",\"sharewhite\",\"sharedomestic\",\"shareunemployed\",\"nvoter\",\"nazivote\"\r\n0.1452451,0.4667877,0.075189"
},
{
"path": "UNCERTAINTY/polls08.csv",
"chars": 50644,
"preview": "\"state\",\"Pollster\",\"Obama\",\"McCain\",\"middate\"\n\"AL\",\"SurveyUSA-2\",36,61,2008-10-27\n\"AL\",\"Capital Survey-2\",34,54,2008-10-"
},
{
"path": "UNCERTAINTY/pres08.csv",
"chars": 1305,
"preview": "\"state.name\",\"state\",\"Obama\",\"McCain\",\"EV\"\n\"Alabama\",\"AL\",39,60,9\n\"Alaska\",\"AK\",38,59,3\n\"Arizona\",\"AZ\",45,54,10\n\"Arkansa"
},
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"path": "UNCERTAINTY/published.csv",
"chars": 679,
"preview": "\"id.p\",\"cond.s\",\"out.s\",\"cond.p\",\"out.p\"\n4,4,4,4,2\n8,2,20,2,20\n11,4,5,4,2\n12,3,5,3,3\n22,3,18,3,7\n24,2,7,2,2\n25,2,10,1,8\n"
},
{
"path": "UNCERTAINTY/resume.csv",
"chars": 133351,
"preview": "\"firstname\",\"sex\",\"race\",\"call\"\n\"Allison\",\"female\",\"white\",0\n\"Kristen\",\"female\",\"white\",0\n\"Lakisha\",\"female\",\"black\",0\n\""
},
{
"path": "UNCERTAINTY/uncertainty-tidy.R",
"chars": 32599,
"preview": "## ----echo = FALSE, warning=FALSE, message=FALSE-----------\nlibrary(tidyverse)\nset.seed(1234)\n\n\n## --------------------"
},
{
"path": "UNCERTAINTY/uncertainty-tidy.Rmd",
"chars": 23817,
"preview": "---\ntitle: 'Code for QSS tidyverse Chapter 7: Uncertainty'\nauthor: \"Kosuke Imai and Nora Webb Williams\"\ndate: \"First Pri"
},
{
"path": "UNCERTAINTY/uncertainty.R",
"chars": 18925,
"preview": "## ------------------------------------------------------------------------\n## simulation parameters\nn <- 100 # sample s"
},
{
"path": "UNCERTAINTY/uncertainty.Rmd",
"chars": 19120,
"preview": "---\ntitle: 'Code for QSS Chapter 7: Uncertainty'\nauthor: \"Kosuke Imai\"\ndate: \"First Printing\"\noutput:\n pdf_document: de"
},
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"path": "UNCERTAINTY/women.csv",
"chars": 4533,
"preview": "\"GP\",\"village\",\"reserved\",\"female\",\"irrigation\",\"water\"\n1,2,1,1,0,10\n1,1,1,1,5,0\n2,2,1,1,2,2\n2,1,1,1,4,31\n3,2,0,0,0,0\n3,"
},
{
"path": "errata/QSS_tidyverse_errata.Rmd",
"chars": 2900,
"preview": "---\ntitle: 'Errata for *Quantitative Social Science: An Introduction in tidyverse* (Princeton University Press)'\nauthor:"
},
{
"path": "errata/QSSerrata.Rmd",
"chars": 13347,
"preview": "---\ntitle: 'Errata for *Quantitative Social Science: An Introduction* (Princeton University Press)'\nauthor: \"Kosuke Imai"
},
{
"path": "syllabus/README.md",
"chars": 546,
"preview": "# Sample syllabi \n1. *POL345/SOC301* An introductory statistics course for social science majors at Princeton ([pdf](pol"
},
{
"path": "syllabus/RcampPrinceton.tex",
"chars": 8660,
"preview": "\\documentclass[12pt]{article}\n\\usepackage[left=1in,top=.8in,right=1in,bottom=.8in,nohead]{geometry}\n\\usepackage{graphicx"
},
{
"path": "syllabus/calendar.sty",
"chars": 3489,
"preview": "\\NeedsTeXFormat{LaTeX2e}\n\n\\def\\CalendarVersion{3.1}\n\\def\\CalendarVersionDate{2009/04/24}\n\n\\ProvidesClass{calendar}[\\Cale"
},
{
"path": "syllabus/pol245Princeton.tex",
"chars": 23788,
"preview": "%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \r\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% P"
},
{
"path": "syllabus/pol345soc305Princeton.tex",
"chars": 23684,
"preview": "\\documentclass[11pt]{article}\n\n% == margins\n\\addtolength{\\hoffset}{-0.75in} \\addtolength{\\voffset}{-0.75in}\n\\addtolength"
},
{
"path": "test.R",
"chars": 174,
"preview": "#!/usr/bin/env Rscript\n\nfor (fn in list.files(\".\", recursive=TRUE, pattern=\".Rmd\")) {\n rmarkdown::render(fn, \"html_do"
}
]
// ... and 3 more files (download for full content)
About this extraction
This page contains the full source code of the kosukeimai/qss GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 197 files (54.3 MB), approximately 14.2M tokens. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
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