library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(ggplot2)
I am interested in analyzing if the increasing distrust in the media(media_2019) influences the feelings and actions of US citizens.This analysis will include registering to vote(votereg_2019), confidence in institutions(inst_court_2019, inst_FBI_2019), and feelings toward black men(bm_2019).
voter_2019<-read.csv("C:/Users/12055/Documents/CUNY - Undergrad/Spring 2021 - CUNY/Data 333/Assignments/Recoding Variables/Data/Voter Data 2019.csv")
Voter_2019<-voter_2019%>%
mutate(FakeMedia= ifelse(media_2019==8, NA,
ifelse(media_2019<3," Agree",
ifelse(media_2019>2,"Disagree", NA))),
VoterRegStatus= ifelse(votereg_2019==1,"Yes",
ifelse(votereg_2019==2,"No", NA)),
ConfidenceSupreme= ifelse(inst_court_2019==1,"A great deal",
ifelse(inst_court_2019==2,"Quite a lot",
ifelse(inst_court_2019==3,"Some",
ifelse(inst_court_2019==4,"Very Little", NA)))),
ConfidenceFBI= ifelse(inst_FBI_2019==1,"A great deal",
ifelse(inst_FBI_2019==2,"Quite a lot",
ifelse(inst_FBI_2019==3,"Some",
ifelse(inst_FBI_2019==4,"Very Little", NA)))),
FeelingBlackmen= ifelse(bm_2019==100, bm_2019,
ifelse(bm_2019<100, bm_2019,
ifelse (bm_2019 >100,NA, NA
))))%>%
select(FakeMedia, VoterRegStatus, ConfidenceSupreme, ConfidenceFBI, FeelingBlackmen)
Voter_2019=na.omit(Voter_2019)
head(Voter_2019)
## FakeMedia VoterRegStatus ConfidenceSupreme ConfidenceFBI FeelingBlackmen
## 1 Disagree Yes Some Quite a lot 50
## 5 Agree Yes A great deal A great deal 90
## 12 Disagree Yes Quite a lot A great deal 97
## 14 Disagree Yes Some A great deal 80
## 16 Agree Yes Some Some 69
## 18 Agree Yes Quite a lot Some 21
tail(Voter_2019)
## FakeMedia VoterRegStatus ConfidenceSupreme ConfidenceFBI FeelingBlackmen
## 9517 Agree Yes Some Some 10
## 9521 Agree No A great deal A great deal 71
## 9525 Disagree Yes Quite a lot Some 86
## 9534 Agree Yes Some Very Little 50
## 9543 Disagree Yes Some Quite a lot 58
## 9544 Agree Yes Quite a lot Quite a lot 90