R: Check Text For Potential Problems

check_text {textclean} | R Documentation

## Check Text For Potential Problems

### Description

`check_text` - Uncleaned text may result in errors, warnings, and incorrect results in subsequent analysis. `check_text` checks text for potential problems and suggests possible fixes. Potential text anomalies that are detected include: factors, missing ending punctuation, empty cells, double punctuation, non-space after comma, no alphabetic characters, non-ASCII, missing value, and potentially misspelled words.

`available_check` - Provide a data.frame view of all the available checks in the `check_text` function.

### Usage

    check_text(x, file = NULL, checks = NULL, n = 10, ...)

    available_checks()

### Arguments

`x` | The text variable.
`file` | A connection, or a character string naming the file to print to. If `NULL` prints to the console. Note that this is assigned as an attribute and passed to `print`.
`checks` | A vector of checks to include from `which_are`. If `checks = NULL`, all checks from `which_are` which be used. Note that all meta checks will be conducted (see `which_are` for details on meta checks).
`n` | The number of affected elements to print out (the rest are truncated).
`...` | ignored.

### Value

Returns a list with the following potential text faults report:

- contraction- Text elements that contain contractions

- date- Text elements that contain dates

- digit- Text elements that contain digits/numbers

- email- Text elements that contain email addresses

- emoticon- Text elements that contain emoticons

- empty- Text elements that contain empty text cells (all white space)

- escaped- Text elements that contain escaped back spaced characters

- hash- Text elements that contain Twitter style hash tags (e.g., #rstats)

- html- Text elements that contain HTML markup

- incomplete- Text elements that contain incomplete sentences (e.g., uses ending punctuation like ...)

- kern- Text elements that contain kerning (e.g., 'The B O M B!')

- list_column- Text variable that is a list column

- missing_value- Text elements that contain missing values

- misspelled- Text elements that contain potentially misspelled words

- no_alpha- Text elements that contain elements with no alphabetic (a-z) letters

- no_endmark- Text elements that contain elements with missing ending punctuation

- no_space_after_comma- Text elements that contain commas with no space afterwards

- non_ascii- Text elements that contain non-ASCII text

- non_character- Text variable that is not a character column (likely `factor`)

- non_split_sentence- Text elements that contain unsplit sentences (more than one sentence per element)

- tag- Text elements that contain Twitter style handle tags (e.g., @trinker)

- time- Text elements that contain timestamps

- url- Text elements that contain URLs

### Note

The output is a list containing meta checks and elemental checks but prints as a pretty formatted output with potential problem elements, the accompanying text, and possible suggestions to fix the text.

[Package textclean version 0.9.3 Index]