Skim meaning9/27/2023 ![]() ![]() You can alsoįurther work with a skim_df using dplyr functions in a pipeline. Within skim to select or drop specific columns for summary. This means that you can use tidyselect helpers Skim() is designed to operate in pipes and to generally play nicely with The first function splits it into a list, with each entryĬorresponding to a data type. See partition() and yank() for methods for transforming this wide dataįrame. Summary statistics all begin numeric for factor summary statistics ![]() ![]() Skimr uses a type namespace for all summary statistics. The data frame produced by skim is wide and sparse. Skim(), but you can replace it with the skim argument. If you just want to see the printed output, call skim_tee() instead. Get_default_skimmers() for a list of default functions. See skim_with() for more details on customizing skim() and The "base" skimmers ( n_missing andĬomplete_rate) are the only columns that don't follow this behavior. skim() computes statistics by data type, and it One unusual feature of this data frame is pseudo. Each call produces a skim_df, which is a fundamentally a tibble with a ![]()
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