# climate SC
#### stochastic dominance ####

library(generalCorr)
library(tidyverse)
library(dplyr)
library(tictoc)
library(robustHD)

# replace PATH accordingly

tweets_daily_2007_2014 <- read.csv("C:/PATH/tweets_daily_2007_2014.csv")
tweets_daily_2015_2019 <- read.csv("C:/PATH/tweets_daily_2015_2019.csv")
tweets_daily_2007_2019 <- read.csv("C:/PATH/tweets_daily_2007_2019.csv")
tweets_weekly_2007_2014 <- read.csv("C:/PATH/tweets_weekly_2007_2014.csv")
tweets_weekly_2007_2019 <- read.csv("C:/PATH/tweets_weekly_2007_2019.csv")
tweets_weekly_2015_2019 <- read.csv("C:/PATH/tweets_weekly_2015_2019.csv")

tic()

s <- tweets_daily_2007_2014
s$X.D..Drought <- NULL
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary0(v)#fast causality analysis
    sink('daily2007_2014.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}

s <- tweets_daily_2015_2019
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary(v)#fast causality analysis
    sink('daily2015_2019.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}


s <- tweets_daily_2007_2019
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary(v)#fast causality analysis
    sink('daily2007_2019.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}

s <- tweets_weekly_2007_2014
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary0(v)#fast causality analysis
    sink('weekly2007_2014.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}

s <- tweets_weekly_2015_2019
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary0(v)#fast causality analysis
    sink('weekly2015_2019.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}


s <- tweets_weekly_2007_2019
s$date <- NULL

for (k in 1:ncol(s)) {
  tryCatch({
    v <- s %>% relocate(k) 
    c1=causeSummary(v)#fast causality analysis
    sink('weekly2007_2019.txt', append = TRUE)
    print(c1)
    xtable(c1)
    sink()
    
  }, 
  
  error=function(z){return(NA)})
  
}

toc()