The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Describe

Roland Krasser

2024-11-12

The explore package offers a simplified way to describe data.

We use synthetic data in this example

library(dplyr)
library(explore)

data <- create_data_buy(obs = 100)
glimpse(data)
#> Rows: 100
#> Columns: 13
#> $ period          <int> 202012, 202012, 202012, 202012, 202012, 202012, 202012~
#> $ buy             <int> 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, ~
#> $ age             <int> 48, 68, 45, 50, 59, 60, 66, 56, 70, 47, 71, 40, 47, 92~
#> $ city_ind        <int> 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, ~
#> $ female_ind      <int> 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, ~
#> $ fixedvoice_ind  <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, ~
#> $ fixeddata_ind   <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ~
#> $ fixedtv_ind     <int> 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, ~
#> $ mobilevoice_ind <int> 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, ~
#> $ mobiledata_prd  <chr> "NO", "NO", "NO", "NO", "NO", "MOBILE STICK", "MOBILE ~
#> $ bbi_speed_ind   <int> 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, ~
#> $ bbi_usg_gb      <int> 79, 60, 82, 52, 54, 64, 52, 73, 36, 90, 78, 103, 52, 2~
#> $ hh_single       <int> 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ~

Describe table

data %>% describe_tbl()
#> 100 observations with 13 variables
#> 0 observations containing missings (NA)
#> 0 variables containing missings (NA)
#> 2 variables with no variance

Describe all variables

data %>% describe_all()
#> # A tibble: 13 x 8
#>    variable        type     na na_pct unique    min      mean    max
#>    <chr>           <chr> <int>  <dbl>  <int>  <dbl>     <dbl>  <dbl>
#>  1 period          int       0      0      1 202012 202012    202012
#>  2 buy             int       0      0      2      0      0.53      1
#>  3 age             int       0      0     41     24     52.6      92
#>  4 city_ind        int       0      0      2      0      0.49      1
#>  5 female_ind      int       0      0      2      0      0.53      1
#>  6 fixedvoice_ind  int       0      0      2      0      0.08      1
#>  7 fixeddata_ind   int       0      0      1      1      1         1
#>  8 fixedtv_ind     int       0      0      2      0      0.43      1
#>  9 mobilevoice_ind int       0      0      2      0      0.68      1
#> 10 mobiledata_prd  chr       0      0      3     NA     NA        NA
#> 11 bbi_speed_ind   int       0      0      2      0      0.6       1
#> 12 bbi_usg_gb      int       0      0     56     10   1064.   100000
#> 13 hh_single       int       0      0      2      0      0.29      1
data %>% 
  describe_all() %>%
  filter(unique == 1)
#> # A tibble: 2 x 8
#>   variable      type     na na_pct unique    min   mean    max
#>   <chr>         <chr> <int>  <dbl>  <int>  <dbl>  <dbl>  <dbl>
#> 1 period        int       0      0      1 202012 202012 202012
#> 2 fixeddata_ind int       0      0      1      1      1      1

Describe one variable

data %>% describe(age)
#> variable = age
#> type     = integer
#> na       = 0 of 100 (0%)
#> unique   = 41
#> min|max  = 24 | 92
#> q05|q95  = 33.85 | 71
#> q25|q75  = 45 | 60
#> median   = 52.5
#> mean     = 52.55
data %>% describe(buy)
#> variable = buy
#> type     = integer
#> na       = 0 of 100 (0%)
#> unique   = 2
#>        0 = 47 (47%)
#>        1 = 53 (53%)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.