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File:US polls 2016.svg

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Original file (SVG file, nominally 810 × 450 pixels, file size: 180 KB)

Summary

Description
English: A combination of nationwide opinion polls during the 2016 U.S. presidential election. The trend lines are Local Regressions with α = 0.8 and 95% confidence interval ribbons. The point sizes and trend lines are weighted according to the margin of error of each poll.
Date
Source Own work
Author Abjiklam

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
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

The graph is generated by the following R script, largely inspired by this file.

library(RCurl)
library(reshape)
library(htmltab)
library(ggplot2)
library(stringr)
library(scales)

#get the table from the url
theurl <- getURL("https://en.wikipedia.org/wiki/Nationwide_opinion_polling_for_the_United_States_presidential_election,_2016", ssl.verifyPeer=FALSE)
table <- htmltab(theurl, which=3)

df = table[, c(2, 8, 3:6)]

names(df) <- c("Date", "Size", "DC", "DP", "RC", "RP")

df = df[which(df$RC=="Donald Trump"), ]
df[which(df$DC=="Bernie Sanders"), ]$DC = "Sanders"
df[which(df$DC=="Hillary Clinton"), ]$DC = "Clinton"
df[which(df$RC=="Donald Trump"), ]$RC = "Trump"
df[which(df$DC=="Sanders" & df$RC=="Trump"), ]$RC = "Trump2"

df$Contest = paste(substr(df$DC, 1, 1), substr(df$RC, 1, 1))

dem.df = df[, c(1:4, 7)]
rep.df = df[, c(1:2, 5:7)]

names(dem.df)[3:4] <- c("Candidate", "Support")
names(rep.df) <- names(dem.df)

df = rbind(dem.df, rep.df)

df$Support = as.numeric(sub("%", "", df$Support))/100

df$Date = sub("[0-9]+\\s*–\\s*([0-9]+)", "\\1", df$Date)
df$Date = sub(".*–", "", df$Date)
df$Date = sub("[0-9]+\\s*-\\s*([0-9]+)", "\\1", df$Date)
df$Date = sub(".*-", "", df$Date)
df$Date = trimws(df$Date)
df$Date = as.Date(df$Date, format="%B %d, %Y")

df$Size = as.numeric(sub(",", "", df$Size))

df$Error = 1/sqrt(df$Size)

cols = c("#6666FF", "#333366", "#FF3333", "#993333")
labs = c("Clinton vs. Trump", "Sanders vs. Trump", "Trump vs. Clinton", "Trump vs. Sanders")

results = df

#breaks() returns n evenly spaced numbers between x and y
#whose squares are divisible by p
#the function is used for the legend
breaks <- function(x, y, n, p) {
  x = sqrt(ceiling(as.integer(x^2) / p) * p)
  y = sqrt(floor(as.integer(y^2) / p) * p)
  s = seq(x, y, length.out=n)
  for (i in 2:(n-1)) {
    s[i] = sqrt(round(s[i]^2 / p) * p)
  }
  return(unique(s))
}

d = ggplot(results, aes(x=Date, y=Support,
                        colour=Candidate, linetype=Candidate, shape=Candidate,
                        size=1/Error, weight=1/Error)) +
  labs(title="Nationwide opinion polling for the 2016 U.S. presidential election") + 
  geom_point(alpha=0.7) + 
  geom_smooth(span=0.8, show.legend=F, alpha=0.2) + 
  scale_colour_manual(name="Candidate", values=cols, labels=labs) + 
  scale_shape_manual(name="Candidate", values=c(16, 15, 16, 15), labels=labs) + 
  scale_linetype_manual(name="Candidate", values=c(1, 5, 1, 5), labels=labs) + 
  scale_size_area(max_size=3,
                  breaks=function(x) breaks(x[1], x[2], 5, 100), #5 numbers divisible by 100
                  labels=function(x) comma_format()(x^2),
                  name="Sample Size") + 
  scale_y_continuous(breaks=seq(0,1,0.05), minor_breaks=seq(0,1,0.01), labels=percent,
                     limits=c(0.34, 0.6)) + 
  scale_x_date(labels=date_format("%b %d"),
               breaks=sort(c(seq(as.Date("2016/1/1"), as.Date("2016/10/1"), "month"),
                             as.Date("2016/11/8")))) +
  theme(panel.grid.minor=element_line(size=0.2),
        panel.grid.major=element_line(size=0.6))

#save plot as "us2016.svg"
svg(filename="us2016.svg", 
    width=9, 
    height=5, 
    pointsize=12,
    bg="transparent")
d
dev.off()

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depicts

2 June 2016

File history

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Date/TimeThumbnailDimensionsUserComment
current14:06, 8 June 2016Thumbnail for version as of 14:06, 8 June 2016810 × 450 (180 KB)Χupdate
01:38, 7 June 2016Thumbnail for version as of 01:38, 7 June 2016810 × 360 (178 KB)Χupdate
17:33, 2 June 2016Thumbnail for version as of 17:33, 2 June 2016810 × 360 (177 KB)Χupdate
00:49, 2 June 2016Thumbnail for version as of 00:49, 2 June 2016810 × 360 (175 KB)ΧUser created page with UploadWizard

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