Pivot table

Calculates aggregates in pivot tables

pvt(df, rows = NULL, cols = NULL, ..., .totals = "Total", .keep_total = "all")

Arguments

df	A dataframe
rows	A vector of variable names that will be on the rows of the pivot table
cols	A vector of variable names that will be on the columns of the pivot table
...	calculations that are passed to `dplyr::summarise()` via the `pivotr::cube()` function
.totals	A string of how output totals are labeled in the rows and cols
.keep_total	one of "all", "overall", "none"

Value

a tibble

Examples

pvt(mtcars, N = n())
#> # A tibble: 1 x 1
#>       N
#>   <int>
#> 1    32
pvt(mtcars, cyl, am, N = n(), Avg = mean(mpg))
#> # A tibble: 4 x 7
#>   cyl     N_0   N_1 N_Total Avg_0 Avg_1 Avg_Total
#>   <chr> <int> <int>   <int> <dbl> <dbl>     <dbl>
#> 1 4         3     8      11  22.9  28.1      26.7
#> 2 6         4     3       7  19.1  20.6      19.7
#> 3 8        12     2      14  15.0  15.4      15.1
#> 4 Total    19    13      32  17.1  24.4      20.1
pvt(mtcars, cyl, am, Avg = mean(wt), N = n())
#> # A tibble: 4 x 7
#>   cyl   Avg_0 Avg_1 Avg_Total   N_0   N_1 N_Total
#>   <chr> <dbl> <dbl>     <dbl> <int> <int>   <int>
#> 1 4      2.94  2.04      2.29     3     8      11
#> 2 6      3.39  2.76      3.12     4     3       7
#> 3 8      4.10  3.37      4.00    12     2      14
#> 4 Total  3.77  2.41      3.22    19    13      32
pvt(mtcars, NULL, am, Avg = mean(wt))
#> # A tibble: 1 x 3
#>     `0`   `1` Total
#>   <dbl> <dbl> <dbl>
#> 1  3.77  2.41  3.22
pvt(mtcars, c(vs, am), cyl, N = n(), .keep_total = "overall")
#> # A tibble: 5 x 6
#>   vs    am      `8`   `4`   `6` Total
#>   <chr> <chr> <int> <int> <int> <int>
#> 1 0     0        12    NA    NA    12
#> 2 0     1         2     1     3     6
#> 3 1     0        NA     3     4     7
#> 4 1     1        NA     7    NA     7
#> 5 Total Total    14    11     7    32