library(readxl) library(plyr) library(dplyr) library(tricky) library(tibble) library(readr) library(knitr)
find_keys()
looks at a table and returns a data frame with the name of all available keys.read_csv( system.file( "extdata", "table_deputes.csv", package = "tricky") ) %>% find_keys()
Many datasets have non standard variable names including accents (ie é, è, à, ...), spaces and so on.
The French IT Dashboard is an example of a data set with column names in natural language :
read_excel( path = system.file( "extdata", "panorama.xlsx", package = "tricky" ) ) %>% names()
set_standard_names
takes a table and returns the same table with standardized namesread_excel( path = system.file( "extdata", "panorama.xlsx", package = "tricky" ) ) %>% set_standard_names() %>% glimpse()
count_na()
returns a table of missing and non-missing values in a vectordetect_na()
returns a table with the number and the share of missing values for each variableread_excel( path = system.file( "extdata", "panorama.xlsx", package = "tricky" ) ) %>% set_standard_names() %>% .$ministere_porteur %>% count_na()
read_excel( path = system.file( "extdata", "panorama.xlsx", package = "tricky" ) ) %>% set_standard_names() %>% detect_na()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.