code_browser_emojis | spanish_emojis_df |
data_param | Helper for consistent documentation of 'data' |
entities | entities |
limpiar_accents | Clean accented characters |
limpiar_alphanumeric | Remove everything except letters, numbers, and spaces |
limpiar_duplicates | Clean the text variable of duplicate posts |
limpiar_emojis_es | Replace emojis with a Spanish textual description |
limpiar_examples | Tibble of examples for LimpiaR functions |
limpiar_ex_subreddits | Quickly extract subreddits from a link variable |
limpiar_inspect | Inspect every post and URL which contains a pattern |
limpiar_link_click | Prepare a URL column to be clickable in Shiny/Data Table |
limpiar_link_click_reverse | Reverses (inverts) limpiar_link_click |
limpiar_na_cols | Clean NA-heavy columns from a Data Frame or Tibble |
limpiar_non_ascii | Remove non-ASCII characters except those with latin accents |
limpiar_pos_annotate | Annotate Texts for Parts of Speech Analysis using udpipe... |
limpiar_pos_import_model | Import UDPipe models to begin Parts of Speech Analysis |
limpiar_pp_companies | Remove known companies for pits & peaks |
limpiar_pp_products | Replace entities for the Peaks&Pit classifier |
limpiar_recode_emojis | Recode emojis with a textual description |
limpiar_remove_emojis | Completely Remove _Most_ Emojis from Text |
limpiar_repeat_chars | Clean repeated charaaaacters |
limpiar_retweets | Clean retweets from the text variable |
limpiar_shorthands | Clean shorthands and abbreviations |
limpiar_slang | Clean slang from multiple Spanish dialects |
limpiar_spaces | Clean redundant spaces |
limpiar_spam_grams | Remove posts containing spam-like n-grams |
limpiar_stopwords | Clean stop words for visualisations |
limpiar_tags | Clean user handles and hashtags |
limpiar_url | Clean URLs from the text variable |
limpiar_wrap | Wrap strings for visual ease |
pipe | Pipe operator |
sentiment_stops | sentiment_stops |
text_var | Helper for consistent documentation of 'text_var' |
topic_stops | topic_stops |
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