desc <- suppressWarnings(readLines("DESCRIPTION")) regex <- "(^Version:\\s+)(\\d+\\.\\d+\\.\\d+)" loc <- grep(regex, desc) ver <- gsub(regex, "\\2", desc[loc]) verbadge <- sprintf('<a href="https://img.shields.io/badge/Version-%s-orange.svg"><img src="https://img.shields.io/badge/Version-%s-orange.svg" alt="Version"/></a></p>', ver, ver) verbadge <- '' ```` ```r library(knitr) knit_hooks$set(htmlcap = function(before, options, envir) { if(!before) { paste('<p class="caption"><b><em>',options$htmlcap,"</em></b></p>",sep="") } }) knitr::opts_knit$set(self.contained = TRUE, cache = FALSE) knitr::opts_chunk$set(fig.path = "tools/figure/")
textplot is a suite of text plotting tools that enable the user to analyze text data via serveral common text plotting methods. Methods include lexical dispersion plots, word trees, speech networks, co-occurrence networks, speech Gantt charts, text hilighting, and word clouds.
To download the development version of textplot:
Download the zip ball or tar ball, decompress and run R CMD INSTALL
on it, or use the pacman package to install the development version:
if (!require("pacman")) install.packages("pacman") pacman::p_load_current_gh("trinker/textplot")
if (!require("pacman")) install.packages("pacman") pacman::p_load(dplyr, magrittr, textplot) pacman::p_load_current_gh('trinker/numform')
sam_i_am %>% lexical_dispersion(c(' not ', ' eat ', ' sam ', ' (sam|eat) ')) %>% plot()
pres_debates2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %$% lexical_dispersion(text.var = dialogue, term.list = wrds, grouping.var = person, rm.var = time ) %>% plot() + ggplot2::scale_x_continuous(labels = numform::ff_denom())
pres_debates2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %$% lexical_dispersion(text.var = dialogue, term.list = wrds, grouping.var = person, rm.var = time ) %>% plot(bg.color = "black", grouping.var = list(fam.aff, sex), color = "yellow", total.color = "white", horiz.color="grey20" ) + ggplot2::scale_x_continuous(labels = numform::ff_denom())
word_tree(sam_i_am, word = 'I') %>% plot()
word_tree(sam_i_am, word = 'do') %>% plot()
presidential_debates_2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %$% word_tree( text.var = dialogue, word = 'america', grouping.var = person ) %>% plot()
hilighter_cols %>% view_cols()
map1 <- list( `#FF69B4` = c('we(\'[a-z]+)?\\b'), `#7CFC00` = c('he(\'[a-z]+)?\\b'), yellow = 'you', gray70 = '\\bi(?=$|\\s)' ) set.seed(10) presidential_debates_2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %>% dplyr::group_by(person) %>% dplyr::sample_n(15) %$% hilight_term(dialogue, map1, list(person)) %>% plot()
map2 <- list( `#FF69B4` = c('talk', 'you'), `#7CFC00` = c('he', "he's"), orange = c('we\'re', 'we'), yellow = 'that', gray70 = c('.', '?', '!') ) set.seed(10) presidential_debates_2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %>% dplyr::group_by(person) %>% dplyr::sample_n(15) %$% hilight_token(dialogue, map2, list(person)) %>% plot()
map3 <- list( 'think', c('he is', "he's", 'you(\'[vr]e)?\\b'), '\\bi\\b' ) %>% map_cols(rev(hilighter_cols)) set.seed(10) presidential_debates_2012 %>% dplyr::filter(person %in% c('ROMNEY', 'OBAMA')) %>% dplyr::group_by(person) %>% dplyr::sample_n(15) %$% hilight_sentence(dialogue, map3, list(person)) %>% plot()
You are welcome to:
- submit suggestions and bug-reports at: https://github.com/trinker/textplot/issues
- send a pull request on: https://github.com/trinker/textplot
- compose a friendly e-mail to: tyler.rinker@gmail.com
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