File:Delegate count for the 2016 Republican Party presidential primaries-2016-04-29.svg
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Summary
[edit]DescriptionDelegate count for the 2016 Republican Party presidential primaries-2016-04-29.svg |
English: Delegate count for the 2016 Republican Party presidential primaries. Graph may not reflect the latest developments. Graph generated with an R script. |
Date | |
Source | Own work, adapted from File:Delegate count for the 2016 Republican Party presidential primaries.svg |
Author | Kaahbonk |
Licensing
[edit]I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Code
[edit]The graph is generated by the following R script:
library(RCurl)
library(reshape)
library(htmltab)
library(ggplot2)
library(stringr)
#get the table from the url
theurl <- getURL("https://en.wikipedia.org/wiki/Results_of_the_Republican_Party_presidential_primaries,_2016", ssl.verifyPeer=FALSE)
table <- htmltab(theurl, which=7)
#keep only the useful columns and name them
df <- table[3:61, 1:ncol(table)-1]
names(df)[1:2] <- c("Date", "State")
#extract delegate count
for (i in 3:ncol(df)) {
df[[i]] = str_extract_all(df[[i]], "[0-9,]+ delegate")
df[[i]] = as.numeric(str_extract(df[[i]], "[0-9,]+"))
df[is.na(df)] = 0
}
#sum up minor candidates
df[[7]] = rowSums(df[,7:14], na.rm=TRUE)
names(df)[7] = "Others"
df = df[,1:7]
#extract state names
df[[2]] = str_replace(df[[2]], "Binding[A-Za-z ]+", "")
df[[2]] = str_replace(df[[2]], "Territorial[A-Za-z ]+", "")
df[[2]] = str_replace(df[[2]], "State[A-Za-z ]+", "")
df[[2]] = str_replace(df[[2]], "District Co[A-Za-z ]+", "")
df[[2]] = str_replace(df[[2]], "Conv[A-Za-z ]+", "")
#extract date
df$Date = as.Date(df$Date, format="%b %d")
#order dates
df=df[order(as.Date(df$Date, format="%d/%m/%Y")),]
#remove contests that haven't happened
df = df[rowSums(df[,3:7], na.rm=TRUE)!=0,]
#new dataframes for unique dates and cumulative count
df2 = data.frame(Date=unique(df$Date))
df3 = df2
for (i in 3:7) {
df2[[names(df)[i]]] = rep(NA, length(df2$Date))
df3[[names(df)[i]]] = rep(NA, length(df2$Date))
for (j in 1:length(df2$Date)) {
df2[[names(df)[i]]][j] = sum(subset(df, Date==df2$Date[j])[[names(df)[i]]])
df3[[names(df)[i]]][j] = sum(df2[[names(df)[i]]][1:j])
}
}
#reshape data so that candidate becomes a variable
mdata <- melt(df2, id=c("Date"))
mdata2 <- melt(df3, id=c("Date"))
names(mdata) <- c("Date", "Candidate", "Delegates")
mdata[["Cumulative"]] <- mdata2[, 3]
results = mdata
#nomination threshold
nomination <- data.frame(yintercept=1237, nomination=factor(1237))
#colors
colors <- c("#283681", "#DAA520", "#29AB87", "#C60E3B", "#000000")
labels = c("Trump", "Cruz", "Kasich", "Rubio", "Other")
#generate plot
d <- ggplot(results, aes(x=Date, y=Cumulative, group=Candidate, colour=Candidate)) +
geom_hline(aes(yintercept=yintercept, linetype=nomination), data=nomination, show.legend=TRUE) +
geom_path() +
geom_point() +
scale_color_manual(values=colors, labels=labels) +
scale_linetype_manual(values=c("dashed")) +
labs(x="Date", y="Delegates", title="Cumulative delegate count", linetype="Nomination")
#display plot
d
File history
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Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 05:16, 22 May 2016 | 454 × 311 (22 KB) | Byteflush (talk | contribs) | Updated to results as of May 17th | |
20:14, 29 April 2016 | 454 × 311 (123 KB) | Kaahbonk (talk | contribs) | User created page with UploadWizard |
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