R_Bridge_HW2

The data set:

For this Homework assignment, I will be using the wvs_justifbribe data set. A data set on attitudes about the justifiability of bribe-taking for all observations in the third to sixth wave of the World Values Survey.

df <- read.csv("justifbribe.csv")
head(df)

1-Overview of the data set:

#Summary
summary(df)

##        X               s002            s003         country         
##  Min.   :     1   Min.   :1.000   Min.   :  8.0   Length:348532     
##  1st Qu.: 87134   1st Qu.:3.000   1st Qu.:246.0   Class :character  
##  Median :174266   Median :4.000   Median :466.0   Mode  :character  
##  Mean   :174266   Mean   :4.274   Mean   :465.6                     
##  3rd Qu.:261399   3rd Qu.:6.000   3rd Qu.:710.0                     
##  Max.   :348532   Max.   :6.000   Max.   :914.0                     
##                                                                     
##       s020           uid              f117      
##  Min.   :1981   Min.   :     1   Min.   : 1.00  
##  1st Qu.:1996   1st Qu.: 87134   1st Qu.: 1.00  
##  Median :2004   Median :174266   Median : 1.00  
##  Mean   :2003   Mean   :174266   Mean   : 1.82  
##  3rd Qu.:2010   3rd Qu.:261399   3rd Qu.: 2.00  
##  Max.   :2016   Max.   :348532   Max.   :10.00  
##                                  NA's   :15532

print("Information for s020: ")

## [1] "Information for s020: "

print(paste("  Mean = ",mean(df$s020, na.rm = TRUE)))

## [1] "  Mean =  2002.52873480771"

print(paste("  Median = ",median(df$s020, na.rm = TRUE) ))

## [1] "  Median =  2004"

print("Information for f117: ")

## [1] "Information for f117: "

print(paste("  Mean = ",mean(df$f117, na.rm = TRUE)))

## [1] "  Mean =  1.81966366366366"

print(paste("  Median = ",median(df$f117, na.rm = TRUE) ))

## [1] "  Median =  1"

2-Creating a subset of the data set:

#Columns
my_df <-subset(df, select = c("country","s020","f117"))

#Rows
my_df <- my_df[my_df$s020 > 2010,]

head(my_df)

3-Make new column name for the new data set:

names(my_df) <- c("country","year","tolerance_score")

4-Overview of the new data set:

The information changed for the year because I only left out survey results from 2010 and onward. The mean of the tolerance score has increased a bit from it’s previous value, I am not sure why yet.

#Summary
summary(my_df)

##    country               year      tolerance_score 
##  Length:83863       Min.   :2011   Min.   : 1.000  
##  Class :character   1st Qu.:2011   1st Qu.: 1.000  
##  Mode  :character   Median :2012   Median : 1.000  
##                     Mean   :2012   Mean   : 1.992  
##                     3rd Qu.:2013   3rd Qu.: 2.000  
##                     Max.   :2016   Max.   :10.000  
##                                    NA's   :1621

print("Information for year: ")

## [1] "Information for year: "

print(paste("  Mean = ",mean(my_df$year, na.rm = TRUE)))

## [1] "  Mean =  2012.25678785638"

print(paste("  Median = ",median(my_df$year, na.rm = TRUE) ))

## [1] "  Median =  2012"

print("Information for tolerance score: ")

## [1] "Information for tolerance score: "

print(paste("  Mean = ",mean(my_df$tolerance_score, na.rm = TRUE)))

## [1] "  Mean =  1.99224240655626"

print(paste("  Median = ",median(my_df$tolerance_score, na.rm = TRUE) ))

## [1] "  Median =  1"

5-Value Change:

my_df$tolerance_score[my_df$tolerance_score == 1] <- "never"
my_df$tolerance_score[my_df$tolerance_score == 10] <- "always"
my_df$tolerance_score[my_df$tolerance_score == 5] <- "neutral"

6-Show changes:

head(my_df[sample(nrow(my_df)), ])

7-Read the new data set from Github:

github_csv_url <- "https://raw.githubusercontent.com/Raharijao/CUNYSPS_SummerBridgeProgram_2023/main/justifbribe.csv"

# Read the CSV file from GitHub
data <- read.csv(github_csv_url)

head(data)