Hugging Face's logo

Datasets:
chuxuan
/
REPRO-Bench

Tasks:
Image-Text-to-Text
Languages:
English
ArXiv:
Tags:
reproducibility
social-science
agents
Dataset card Files
xet
 Community
1
REPRO-Bench / 27 /replication_package /Table6_script.R
anonymous-submission-acl2025's picture
anonymous-submission-acl2025
add 27
3af64c0
Raw History Blame Contribute Delete
2.18 kB
#install packages
# install.packages('plyr')
# install.packages('dplyr')
# install.packages('tidyr')
# install.packages('ggplot2')
# install.packages('multiwayvcov')
# install.packages('lmtest')
# install.packages('stargazer')
rm(list=ls())
library(plyr);library(dplyr, warn.conflicts = F)
library(tidyr)
library(ggplot2)
suppressMessages( library(lmtest) )
suppressMessages( library(multiwayvcov) )
suppressMessages(library(stargazer))
s = function(x){summary(factor(x))}
#setwd() #set working directory
#read data
A = read.csv('4-20-20_deid_nearestK.csv',
na.strings=c('','NA'),strip.white=T,stringsAsFactors = F)
Q = A[which(A$Wave == 'Bangalore 2017'),]
####################################################################################
####################################################################################
#clean data
Aprime = A[A$A.A7_Area.Neighborhood %in% names(which(table(A$A.A7_Area.Neighborhood) >= 30)),]#Drop places with < 30 observations
Aprime = Aprime[which(!is.na(Aprime$A.A7_Area.Neighborhood)),] #drop NA neighborhoods
Aprime = Aprime[which(Aprime$A.A7_Area.Neighborhood != 'Bangalore NA'),] #Still 8273
A = Aprime; rm(Aprime)
####################################################################################
########################################
#Count observations and neighborhoods
#THIS IS BASIS FOR TABLE 6
#2017 neighborhoods
length(levels(factor(Q$A.A7_Area.Neighborhood))) #50
#2017 respondents
nrow(Q) #1948
#Bangalore '16 neighborhoods
length(levels(factor(A$A.A7_Area.Neighborhood[which(A$Wave == 'Bangalore 2016')]))) #20
#Bangalore '16 respondents
nrow(A[which(A$Wave == 'Bangalore 2016'),]) #609
#Jaipur neighborhoods
length(levels(factor(A$A.A7_Area.Neighborhood[which(A$City == 'Jaipur')]))) #45
#Jaipur respondents
nrow(A[which(A$City == 'Jaipur'),]) #2669
#Patna neighborhoods
length(levels(factor(A$A.A7_Area.Neighborhood[which(A$City == 'Patna')]))) #34
#Patna respondents
nrow(A[which(A$City == 'Patna'),]) #1972
#LAST TWO ROWS OF TABLE 6: Network data
N = readRDS('4-20-20_Network-KNearest_DeID_demed.RDS')
nrow(N[which(N$City == 'Jaipur'),]) #1593
nrow(N[which(N$City == 'Patna'),]) #988