The goal of fluid is to provide useful functions for your R programming workflow.
You can install fluid from Github with:
remotes::install_github("markusdumke/fluid")
library(fluid)
summarize(iris)
#> data.frame: 150 x 5
#>
#> Column types:
#> factor numeric
#> 1 4
#>
#> Numeric columns:
#> column type min q_0.25 median mean q_0.75 max n_NA
#> 1: Sepal.Length double 4.3 5.1 5.80 5.843 6.4 7.9 0
#> 2: Sepal.Width double 2.0 2.8 3.00 3.057 3.3 4.4 0
#> 3: Petal.Length double 1.0 1.6 4.35 3.758 5.1 6.9 0
#> 4: Petal.Width double 0.1 0.3 1.30 1.199 1.8 2.5 0
#>
#> Categorical columns:
#> $ Species
#> value N Prop
#> 1: setosa 50 0.333
#> 2: versicolor 50 0.333
#> 3: virginica 50 0.333
#> 4: <NA> 0 0.000
library(nycflights13)
flights$carrier %>% freq_table(.cum = TRUE)
#> Lumped together 7 categories to Other.
#> .x N Prop Cum.N Cum.Prop
#> 1: UA 58665 0.174 58665 0.174
#> 2: B6 54635 0.162 113300 0.336
#> 3: EV 54173 0.161 167473 0.497
#> 4: DL 48110 0.143 215583 0.640
#> 5: AA 32729 0.097 248312 0.737
#> 6: MQ 26397 0.078 274709 0.815
#> 7: US 20536 0.061 295245 0.876
#> 8: 9E 18460 0.055 313705 0.931
#> 9: WN 12275 0.036 325980 0.967
#> 10: Other 10796 0.032 336776 0.999
#> 11: <NA> 0 0.000 336776 0.999
seq_date("2019-01-01", "2019-12-31", .by = "month")
#> [1] "2019-01-01" "2019-02-01" "2019-03-01" "2019-04-01" "2019-05-01"
#> [6] "2019-06-01" "2019-07-01" "2019-08-01" "2019-09-01" "2019-10-01"
#> [11] "2019-11-01" "2019-12-01"
seq_date("2019-01-01", .length.out = 10)
#> [1] "2019-01-01" "2019-01-02" "2019-01-03" "2019-01-04" "2019-01-05"
#> [6] "2019-01-06" "2019-01-07" "2019-01-08" "2019-01-09" "2019-01-10"
seq_date("2018-09-01", "2018-09-10", .by = 2L)
#> [1] "2018-09-01" "2018-09-03" "2018-09-05" "2018-09-07" "2018-09-09"
seq_date("2018-09-01", "2018-09-05")
#> [1] "2018-09-01" "2018-09-02" "2018-09-03" "2018-09-04" "2018-09-05"
seq_row(mtcars)
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
#> [24] 24 25 26 27 28 29 30 31 32
seq_col(mtcars)
#> [1] 1 2 3 4 5 6 7 8 9 10 11
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