D607_A1_RickS
Rick S
8/29/2020
Overview
Voting is an important civic duty in a democracy. Registered voters can participate in federal, state, and local elections. Presidential elections, held every 4 years, are important major national events. There are many get out the vote campaigns preceded by voter registration drives. While voter registrations for the 2020 election cycle was exceeding the corresponding 2016 election cycle, the COVID-19 global pandemic has adversely affected this process (Rogers & Rakich, 2020).
Reference: Rogers, K., & Rakich, N. (2020, Jun 26). Voter registrations are way, way down during the pandemic. Retrieved from https://fivethirtyeight.com/features/voter-registrations-are-way-way-down-during-the-pandemic/.
theURL <- "https://raw.githubusercontent.com/fivethirtyeight/data/master/voter-registration/new-voter-registrations.csv"
new_voter_regs_DF <- read.table(file=theURL, header=TRUE, sep=",")
dim(new_voter_regs_DF)## [1] 106 4str(new_voter_regs_DF)## 'data.frame': 106 obs. of 4 variables:
## $ Jurisdiction : chr "Arizona" "Arizona" "Arizona" "Arizona" ...
## $ Year : int 2016 2016 2016 2016 2020 2020 2020 2020 2016 2016 ...
## $ Month : chr "Jan" "Feb" "Mar" "Apr" ...
## $ New.registered.voters: int 25852 51155 48614 30668 33229 50853 31872 10249 87574 103377 ...head(new_voter_regs_DF)## Jurisdiction Year Month New.registered.voters
## 1 Arizona 2016 Jan 25852
## 2 Arizona 2016 Feb 51155
## 3 Arizona 2016 Mar 48614
## 4 Arizona 2016 Apr 30668
## 5 Arizona 2020 Jan 33229
## 6 Arizona 2020 Feb 50853tail(new_voter_regs_DF)## Jurisdiction Year Month New.registered.voters
## 101 Virginia 2016 May 26239
## 102 Virginia 2020 Jan 25934
## 103 Virginia 2020 Feb 29507
## 104 Virginia 2020 Mar 31492
## 105 Virginia 2020 Apr 5467
## 106 Virginia 2020 May 8239#new_voter_regs_DFData Munging
Changed Jurisdiction to State and “New Registered Voters” to “New Voter Regs”. Modifed Month to include numeric for calendar sequence.
colnames(new_voter_regs_DF)<-c("State","Year","Month","NewVoterRegs")
head(new_voter_regs_DF)## State Year Month NewVoterRegs
## 1 Arizona 2016 Jan 25852
## 2 Arizona 2016 Feb 51155
## 3 Arizona 2016 Mar 48614
## 4 Arizona 2016 Apr 30668
## 5 Arizona 2020 Jan 33229
## 6 Arizona 2020 Feb 50853# sequence month in calendar order
vec <- new_voter_regs_DF$Month
SeqMonth <- function(vec) {
newvec <- vec
for (i in 1:length(vec)) {
if(vec[i] == "Jan") {
newvec [i] <- "01:Jan"
}else if(vec[i] == "Feb") {
newvec [i] <- "02:Feb"
}else if(vec[i] == "Mar") {
newvec [i] <- "03:Mar"
}else if(vec[i] == "Apr") {
newvec [i] <- "04:Apr"
}else if(vec[i] == "May") {
newvec [i] <- "05:May"
}else if(vec[i] == "Jun") {
newvec [i] <- "06:Jun"
}else if(vec[i] == "Jul") {
newvec [i] <- "07:Jul"
}else if(vec[i] == "Aug") {
newvec [i] <- "08:Aug"
}else if(vec[i] == "Sep") {
newvec [i] <- "09:Sep"
}else if(vec[i] == "Oct") {
newvec [i] <- "10:Oct"
}else if(vec[i] == "Noc") {
newvec [i] <- "11:Nov"
}else if(vec[i] == "Dec") {
newvec [i] <- "12:Dec"
}else {
newvec [i] <- "00-???"
}
}
# print (newvec)
return(vec <-newvec)
}
new_voter_regs_DF$Month <- (SeqMonth(vec))Subsetting - Extract 2016 New Voter Registration data
In preparation for graphing, extract 2016 data
# subset some data
df_2016nvr <- subset(new_voter_regs_DF, Year==2016)
head(df_2016nvr)## State Year Month NewVoterRegs
## 1 Arizona 2016 01:Jan 25852
## 2 Arizona 2016 02:Feb 51155
## 3 Arizona 2016 03:Mar 48614
## 4 Arizona 2016 04:Apr 30668
## 9 California 2016 01:Jan 87574
## 10 California 2016 02:Feb 103377January through May 2016 New Voter Registrations Line Plots
These line plots show the January through May 2016 New Voter Registrations by State.
g <- ggplot(data=df_2016nvr, aes(x=Month, y=NewVoterRegs))
g <- g + geom_line(aes(color=factor(State), group=State))
g <- g + scale_color_discrete(name="State")
g <- g + scale_y_continuous(labels=comma)
g <- g + labs(title="2016 New Voter Registrations by State", x="Month", y="New Voter Registrations")
g
Subsetting - Extract 2020 New Voter Registration data
In preparation for graphing , extract 2020 data
# subset some data
df_2020nvr <- subset(new_voter_regs_DF, Year==2020)
head(df_2020nvr)## State Year Month NewVoterRegs
## 5 Arizona 2020 01:Jan 33229
## 6 Arizona 2020 02:Feb 50853
## 7 Arizona 2020 03:Mar 31872
## 8 Arizona 2020 04:Apr 10249
## 13 California 2020 01:Jan 151595
## 14 California 2020 02:Feb 238281January through May 2020 New Voter Registrations Line Plots
These line plots show the January through May 2020 New Voter Registrations by State.
g <- ggplot(data=df_2020nvr, aes(x=Month, y=NewVoterRegs))
g <- g + geom_line(aes(color=factor(State), group=State))
g <- g + scale_color_discrete(name="State")
g <- g + scale_y_continuous(labels=comma)
g <- g + labs(title="2020 New Voter Registrations by State", x="Month", y="New Voter Registrations")
g
Subsetting - Extract May 2020 New Voter Registration data
However, only the following 5 States out of 12 reported New Voter Registration data in May 2020.
# subset some data
df_May2020nvr <- subset(new_voter_regs_DF, Year==2020 & Month == "05:May")
head(df_May2020nvr)## State Year Month NewVoterRegs
## 42 District of Columbia 2020 05:May 1925
## 76 Maryland 2020 05:May 23488
## 86 North Carolina 2020 05:May 23517
## 96 Texas 2020 05:May 35678
## 106 Virginia 2020 05:May 8239Conclusions
The COVID-19 Global Pandemic has had a substantial adverse affect on new voter registrations in 2020. While January and February appear comparable in 2016 and 2020, there is a substantial drop in new voter registrations beginning in March 2020 coinciding with emergency federal, state, and local executive actions related to flattening the curve of COVID-19 cases.
As COVID-19 cases within the U.S. and around the globe increased in March through May, one can see the dramatic rise in cases from this Johns Hopkins Coronavirus Critical Trends Graph https://coronavirus.jhu.edu/data/new-cases. One can also observe the trend in confirmed cases by state https://coronavirus.jhu.edu/data/new-cases-50-states.