clessnverse

clessnverse contains functions for data domestication, analysis and visualization along with functions specific to the research chair’s projects.

Installation

To install the latest stable version of this package, run the following line in your R console:

remotes::install_github("clessn/clessnverse")

Usage

library("clessnverse") will load the following packages:

• hublot, to access clHub
• clessnhub, to access clessn hub
• locateip, to locate IP addresses using ip-api.com
• wikirest, to get data from the Wikimedia REST API

Examples

Wrangle data

Normalize a continuous variable between 0 and 1

library(clessnverse)

data <- tibble::tibble(a = c(1, 0, 2, 0), b = c(4, 0, 1, 0))

# Base R
sapply(data, normalize_min_max)
#>        a    b
#> [1,] 0.5 1.00
#> [2,] 0.0 0.00
#> [3,] 1.0 0.25
#> [4,] 0.0 0.00

# Dplyr
library("dplyr")

data %>%
  mutate(across(c(a, b), normalize_min_max))
#> # A tibble: 4 × 2
#>       a     b
#>   <dbl> <dbl>
#> 1   0.5  1   
#> 2   0    0   
#> 3   1    0.25
#> 4   0    0

Analyse data

run_dictionary(
  data.frame(colnames(attitude)),
  text = colnames(attitude),
  dictionary = quanteda::data_dictionary_LSD2015
) %>% head()
#> 0.302 sec elapsed
#>   doc_id negative positive neg_positive neg_negative
#> 1  text1        0        0            0            0
#> 2  text2        1        0            0            0
#> 3  text3        0        1            0            0
#> 4  text4        0        1            0            0
#> 5  text5        0        0            0            0
#> 6  text6        1        0            0            0

Visualise data

library("clessnverse")

p  <- ggplot2::ggplot(data = ggplot2::mpg) +
  ggplot2::geom_point(mapping = ggplot2::aes(x = displ, y = cty, colour = class)) +
  ggplot2::labs(title = "Look at this graph!",
                subtitle = "What a great theme, eh?",
                caption = "Data: API Twitter \nCLESSN") +
  ggplot2::xlab("x axis label") +
  ggplot2::ylab("y axis label")

p + theme_clean_light()

p + theme_clean_dark()

p  <- ggplot2::ggplot(data = ggplot2::mpg) +
  ggplot2::geom_point(mapping = ggplot2::aes(x = displ, y = cty, colour = class)) +
  ggplot2::labs(title = "Look at this graph!",
                subtitle = "What a great look, eh?",
                caption = "Data: Twitter API \nCLESSN")

p + scale_discrete_quorum(aesthetics = "colour")

Issues and suggestions

You can submit bugs or suggestions in the Issues tab of this repo. To facilitate problem solving, please include a minimal reproducible example of the issue.