visdat: vis_expect – R documentation

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vis_expect

Visualise whether a value is in a data frame

Description

vis_expect visualises certain conditions or values in your data. For example, If you are not sure whether to expect -1 in your data, you could write: vis_expect(data, ~.x == -1), and you can see if there are times where the values in your data are equal to -1. You could also, for example, explore a set of bad strings, or possible NA values and visualise where they are using vis_expect(data, ~.x %in% bad_strings) where bad_strings is a character vector containing bad strings like N A N/A etc.

Usage

vis_expect(data, expectation, show_perc = TRUE)

Arguments

`data`	a data.frame
`expectation`	a formula following the syntax: `~.x {condition}`. For example, writing `~.x < 20` would mean "where a variable value is less than 20, replace with NA", and `~.x %in% {vector}` would mean "where a variable has values that are in that vector".
`show_perc`	logical. TRUE now adds in the % of expectations are TRUE or FALSE in the whole dataset into the legend. Default value is TRUE.

Value

a ggplot2 object

Examples

dat_test <- tibble::tribble(
            ~x, ~y,
            -1,  "A",
            0,  "B",
            1,  "C",
            NA, NA
            )

vis_expect(dat_test, ~.x == -1)

## Not run: 
vis_expect(airquality, ~.x == 5.1)

# explore some common NA strings

common_nas <- c(
"NA",
"N A",
"N/A",
"na",
"n a",
"n/a"
)

dat_ms <- tibble::tribble(~x,  ~y,    ~z,
                         1,   "A",   -100,
                         3,   "N/A", -99,
                         NA,  NA,    -98,
                         "N A", "E",   -101,
                         "na", "F",   -1)

vis_expect(dat_ms, ~.x %in% common_nas)


## End(Not run)

visdat

Preliminary Visualisation of Data

v0.5.3

MIT + file LICENSE

Authors

Nicholas Tierney [aut, cre] (<https://orcid.org/0000-0003-1460-8722>), Sean Hughes [rev] (<https://orcid.org/0000-0002-9409-9405>, Sean Hughes reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/87), Mara Averick [rev] (Mara Averick reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/87), Stuart Lee [ctb], Earo Wang [ctb], Nic Crane [ctb]

Initial release