Explore and summarize data

Source: R/explore.R

Explore and summarize data

explore(
  dataset,
  vars = "",
  byvar = "",
  fun = c("mean", "sd"),
  top = "fun",
  tabfilt = "",
  tabsort = "",
  nr = Inf,
  data_filter = "",
  envir = parent.frame()
)

Arguments

dataset

Dataset to explore
vars

(Numeric) variables to summarize
byvar

Variable(s) to group data by
fun

Functions to use for summarizing
top

Use functions ("fun"), variables ("vars"), or group-by variables as column headers
tabfilt

Expression used to filter the table (e.g., "Total > 10000")
tabsort

Expression used to sort the table (e.g., "desc(Total)")
nr

Number of rows to display
data_filter

Expression used to filter the dataset before creating the table (e.g., "price > 10000")
envir

Environment to extract data from

Value

A list of all variables defined in the function as an object of class explore

Details

See https://radiant-rstats.github.io/docs/data/explore.html for an example in Radiant

See also

See summary.explore to show summaries

Examples

explore(diamonds, c("price", "carat")) %>% str()
#> List of 10
#>  $ tab        :'data.frame':	2 obs. of  3 variables:
#>   ..$ variable: Factor w/ 2 levels "price","carat": 1 2
#>   ..$ mean    : num [1:2] 3907.186 0.794
#>   ..$ sd      : num [1:2] 3956.915 0.474
#>   ..- attr(*, "radiant_nrow")= int 2
#>  $ df_name    : chr "diamonds"
#>  $ vars       : chr [1:2] "price" "carat"
#>  $ byvar      : NULL
#>  $ fun        : chr [1:2] "mean" "sd"
#>  $ top        : chr "fun"
#>  $ tabfilt    : chr ""
#>  $ tabsort    : chr ""
#>  $ nr         : num Inf
#>  $ data_filter: chr ""
#>  - attr(*, "class")= chr [1:2] "explore" "list"
explore(diamonds, "price:x")$tab
#>   variable         mean           sd
#> 1    price 3.907186e+03 3956.9154001
#> 2    carat 7.942833e-01    0.4738263
#> 3  clarity 1.333333e-02    0.1147168
#> 4      cut 3.366667e-02    0.1803998
#> 5    color 1.273333e-01    0.3334016
#> 6    depth 6.175267e+01    1.4460279
#> 7    table 5.746533e+01    2.2411022
#> 8        x 5.721823e+00    1.1240545
explore(diamonds, c("price","carat"), byvar = "cut", fun = c("n_missing", "skew"))$tab
#>          cut variable n_missing      skew
#> 1       Fair    price         0 1.5741334
#> 2       Fair    carat         0 0.9285670
#> 3       Good    price         0 1.4885765
#> 4       Good    carat         0 1.0207909
#> 5  Very Good    price         0 1.6007752
#> 6  Very Good    carat         0 0.9370738
#> 7    Premium    price         0 1.4131786
#> 8    Premium    carat         0 0.9299567
#> 9      Ideal    price         0 1.7986601
#> 10     Ideal    carat         0 1.3654745