| Encoding() |
checks or sets the encoding of a character string (base R) |
| as_tibble() |
converts a data frame into a tibble, which prints more neatly (tidyverse) |
| corpus() |
creates a quanteda corpus from a data frame, with text_field specifying the variable containing the texts (quanteda) |
| dfm() |
creates a document-feature matrix from tokens (quanteda) |
| dfm_tfidf() |
weights a document-feature matrix by tf-idf (quanteda) |
| dfm_weight() |
weights the cells of a document-feature matrix, e.g., as proportions with scheme = prop (quanteda) |
| docvars() |
shows the metadata (document variables) of a corpus, tokens object, or DFM (quanteda) |
| featnames() |
returns the names of all features in a document-feature matrix (quanteda) |
| filter() |
keeps only rows that meet a condition (tidyverse) |
| fixed() |
tells stringr functions to interpret a pattern literally instead of as a regular expression (stringr) |
| guess_encoding() |
guesses the encoding of a file (readr) |
| head() |
shows the first rows or elements of an object (base R) |
| install.packages() |
installs an R package (only needed once) (base R) |
| library() |
loads an installed R package (needed every time you restart R) (base R) |
| mutate() |
creates new variables or changes existing ones (tidyverse) |
| ncol() |
counts the number of columns of a data frame (base R) |
| ndoc() |
counts the number of documents in a corpus, tokens object, or DFM (quanteda) |
| nfeat() |
counts the number of features in a document-feature matrix (quanteda) |
| nrow() |
counts the number of rows of a data frame (base R) |
| ntoken() |
counts the number of tokens per document (quanteda) |
| phrase() |
declares a pattern as a multi-word expression, e.g., for tokens_compound() (quanteda) |
| pull() |
extracts a single variable from a data frame as a vector (tidyverse) |
| read.csv() |
reads in comma-separated .csv files (base R) |
| read.csv2() |
reads in semicolon-separated .csv files with commas as decimal separators (base R) |
| select() |
keeps only selected variables (tidyverse) |
| slice() |
keeps rows by their position, e.g., slice(1) for the first row (tidyverse) |
| sparsity() |
returns the share of cells in a document-feature matrix that contain a 0 (quanteda) |
| stopwords() |
returns a ready-made list of stopwords for a language, e.g., stopwords(english) (quanteda) |
| str_count() |
counts how often a pattern occurs in a text (stringr) |
| str_detect() |
checks whether a pattern occurs in a text (TRUE) or not (FALSE) (stringr) |
| str_extract() |
extracts the first match of a pattern (stringr) |
| str_length() |
counts the number of characters in a text (stringr) |
| str_remove_all() |
removes all occurrences of a pattern (stringr) |
| str_replace_all() |
replaces all occurrences of a pattern with something else (stringr) |
| summarise() |
calculates summary statistics, e.g., mean or maximum (tidyverse) |
| summary() |
gives an overview of a corpus, e.g., the number of tokens and types per document (quanteda) |
| tokens() |
tokenizes texts, i.e., breaks them down into features, and can remove punctuation, numbers, and symbols (quanteda) |
| tokens_compound() |
keeps multi-word expressions together as one feature, e.g., new_york (quanteda) |
| tokens_remove() |
removes features from tokens, e.g., stopwords (quanteda) |
| tokens_tolower() |
converts all tokens to lowercase (quanteda) |
| tokens_wordstem() |
reduces tokens to their word stem (quanteda) |