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@@ -5,6 +5,14 @@ find_word <- function(res, word) {
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nrow))
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}
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#'Assign speaker-name to speaker-ID
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#'
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#' Assign speaker-name to speaker-ID.
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#'
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#' @param tb tibble
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#' @param res list of tibbles
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#' @param fraction_only If TRUE select only from "fraction"
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#'
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#' @export
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join_speaker <- function(tb, res, fraction_only = F) {
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joined <- left_join(tb, res$speaker, by=c("speaker" = "id"))
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@@ -30,6 +38,20 @@ party_order <- factor(c("Fraktionslos", "AfD&Fraktionslos",
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"DIE LINKE", "BÜNDNIS 90 / DIE GRÜNEN", "SPD", "CDU/CSU",
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"FDP", "AfD", NA_character_))
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#'Bar chart of the fractions
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#'
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#' @param tb The tibble to be analyzed.
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#' @param x_variable Default is fraction.
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#' @param y_variable Default is n.
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#' @param fill Default is fraction.
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#' @param title Title of the chart.
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#' @param xlab Description of x-Lab. Default is Fraction.
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#' @param ylab Description of y-Lab. Default is n.
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#' @param filllab Default is Fraction.
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#' @param flipped Default is TRUE. If TRUE draw bars horizontally, else vertically.
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#' @param position Default is dodge.
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#' @param reorder Either reorder fraction factor by variable value or reorder fraction factor by party seat order in parliament (default).
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#'
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#' @export
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bar_plot_fractions <- function(tb,
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x_variable = NULL, # default is fraction
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@@ -73,8 +95,15 @@ bar_plot_fractions <- function(tb,
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if (flipped) plt + coord_flip() else plt
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}
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# Counts how many talks do match a given pattern and summarises by date
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#
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#'Word usage summarised by date
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#'
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#' Counts how many talks do match a given pattern and summarises by date.
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#'
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#' @param res List of Tibbles to be analysed.
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#' @param patterns Words to look up.
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#' @param name ?
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#' @param tidy Default is FALSE.
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#'
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#' @export
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word_usage_by_date <- function(res, patterns, name, tidy=F) {
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tb <- res$talks
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@@ -194,7 +194,7 @@ parse_speechlist <- function(speechlist_xml, date) {
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}
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# create a tibble of speaker from a list of xml nodes representing speaker
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parse_speakerliste <- function(speakerliste_xml) {
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parse_speakerlist <- function(speakerliste_xml) {
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d <- sapply(speakerliste_xml, parse_speaker)
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tibble(id = d["id",],
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vorname = d["vorname",],
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@@ -0,0 +1,46 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/analyze.R
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\name{bar_plot_fractions}
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\alias{bar_plot_fractions}
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\title{Bar chart of the fractions}
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\usage{
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bar_plot_fractions(
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tb,
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x_variable = NULL,
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y_variable = NULL,
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fill = NULL,
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title = NULL,
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xlab = "Fraction",
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ylab = "n",
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filllab = "Fraction",
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flipped = TRUE,
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position = "dodge",
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reorder = FALSE
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)
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}
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\arguments{
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\item{tb}{The tibble to be analyzed.}
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\item{x_variable}{Default is fraction.}
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\item{y_variable}{Default is n.}
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\item{fill}{Default is fraction.}
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\item{title}{Title of the chart.}
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\item{xlab}{Description of x-Lab. Default is Fraction.}
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\item{ylab}{Description of y-Lab. Default is n.}
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\item{filllab}{Default is Fraction.}
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\item{flipped}{Default is TRUE. If TRUE draw bars horizontally, else vertically.}
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\item{position}{Default is dodge.}
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\item{reorder}{Either reorder fraction factor by variable value or reorder fraction factor by party seat order in parliament (default).}
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}
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\description{
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Bar chart of the fractions
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}
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@@ -0,0 +1,18 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/analyze.R
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\name{join_speaker}
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\alias{join_speaker}
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\title{Assign speaker-name to speaker-ID}
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\usage{
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join_speaker(tb, res, fraction_only = F)
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}
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\arguments{
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\item{tb}{tibble}
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\item{res}{list of tibbles}
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\item{fraction_only}{If TRUE select only from "fraction"}
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}
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\description{
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Assign speaker-name to speaker-ID.
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}
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@@ -0,0 +1,16 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/analyze.R
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\docType{data}
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\name{party_colors}
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\alias{party_colors}
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\title{Assignment of the official colors to the parties}
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\format{
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An object of class \code{character} of length 8.
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}
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\usage{
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party_colors
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}
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\description{
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Assignment of the official colors to the parties
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}
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\keyword{datasets}
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@@ -0,0 +1,20 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/analyze.R
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\name{word_usage_by_date}
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\alias{word_usage_by_date}
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\title{Word usage summarised by date}
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\usage{
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word_usage_by_date(res, patterns, name, tidy = F)
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}
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\arguments{
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\item{res}{List of Tibbles to be analysed.}
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\item{patterns}{Words to look up.}
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\item{name}{?}
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\item{tidy}{Default is FALSE.}
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}
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\description{
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Counts how many talks do match a given pattern and summarises by date.
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}
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@@ -88,7 +88,9 @@ text %>%
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str_trim() ->
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names
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gender <- tibble(name = names,
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gender <- tibble(speaker = names,
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gender = gender)
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```
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