summary method for panel_data objects.
Usage
# S3 method for panel_data
summary(object, ..., by.wave = TRUE, by.id = FALSE, skim_with = NULL)Arguments
- object
A
panel_dataframe.- ...
Optionally, unquoted variable names/expressions separated by commas to be passed to
dplyr::select(). Otherwise, all columns are included.- by.wave
(if
skimris installed) Separate descriptives by wave? Default is TRUE.- by.id
(if
skimris installed) Separate descriptives by entity? Default is FALSE. Be careful if you have a large number of entities as the output will be massive.- skim_with
A closure from
skimr::skim_with(). If set, skim
Examples
data("WageData")
wages <- panel_data(WageData, id = id, wave = t)
summary(wages, lwage, exp, wks)
#> Loading required namespace: skimr
#>
#> ── Variable type: numeric ──────────────────────────────────────────────────────
#> skim_variable t n_missing complete_rate mean sd p0 p25 p50 p75
#> 1 lwage 1 0 1 6.38 0.388 5.01 6.12 6.42 6.65
#> 2 lwage 2 0 1 6.47 0.363 5.01 6.24 6.53 6.75
#> 3 lwage 3 0 1 6.60 0.447 4.61 6.33 6.61 6.86
#> 4 lwage 4 0 1 6.70 0.441 5.08 6.44 6.72 6.96
#> 5 lwage 5 0 1 6.79 0.424 5.27 6.51 6.80 7.04
#> 6 lwage 6 0 1 6.86 0.424 5.66 6.60 6.91 7.11
#> 7 lwage 7 0 1 6.95 0.438 5.68 6.68 6.98 7.21
#> 8 exp 1 0 1 16.9 10.8 1 7 15 26
#> 9 exp 2 0 1 17.9 10.8 2 8 16 27
#> 10 exp 3 0 1 18.9 10.8 3 9 17 28
#> 11 exp 4 0 1 19.9 10.8 4 10 18 29
#> 12 exp 5 0 1 20.9 10.8 5 11 19 30
#> 13 exp 6 0 1 21.9 10.8 6 12 20 31
#> 14 exp 7 0 1 22.9 10.8 7 13 21 32
#> 15 wks 1 0 1 46.3 6.25 6 46 48 50
#> 16 wks 2 0 1 47.0 5.13 11 47 49 50
#> 17 wks 3 0 1 47.0 4.77 20 47 49 50
#> 18 wks 4 0 1 47.2 4.46 8 47 48 50
#> 19 wks 5 0 1 47.0 4.89 6 47 48 50
#> 20 wks 6 0 1 46.7 4.98 6 46 48 50
#> 21 wks 7 0 1 46.5 5.19 5 46 48 49
#> p100 hist
#> 1 6.91 ▁▂▃▇▇
#> 2 6.91 ▁▁▂▅▇
#> 3 8.27 ▁▂▇▃▁
#> 4 8.52 ▁▃▇▂▁
#> 5 8.10 ▁▂▇▅▁
#> 6 8.16 ▁▃▇▃▁
#> 7 8.54 ▁▅▇▂▁
#> 8 45 ▇▇▅▅▁
#> 9 46 ▇▇▅▅▁
#> 10 47 ▇▇▅▅▁
#> 11 48 ▇▇▅▅▁
#> 12 49 ▇▇▅▅▁
#> 13 50 ▇▇▅▅▁
#> 14 51 ▇▇▅▅▁
#> 15 52 ▁▁▁▁▇
#> 16 52 ▁▁▁▁▇
#> 17 52 ▁▁▁▁▇
#> 18 52 ▁▁▁▁▇
#> 19 52 ▁▁▁▁▇
#> 20 52 ▁▁▁▁▇
#> 21 52 ▁▁▁▁▇