Manipulate pivot tables
pivot_rows(.data, ...) pivot_columns(.data, ...)
| .data | A data.frame or a pivot_prep object |
|---|---|
| ... | Variables or calculation to group by |
retail_orders %>% pivot_rows(status) %>% pivot_columns(country) %>% pivot_values(total_sales = sum(sales))#> Australia Austria Belgium Canada Denmark Finland France Germany Ireland Italy Japan Norway Philippines Singapore Spain Sweden Switzerland UK USA Total #> Cancelled 50010.65 48710.92 50408.25 45357.66 194487.48 #> Disputed 14378.09 26012.87 31821.9 72212.86 #> In Process 43971.43 8411.95 43784.69 35133.34 13428.55 144729.96 #> On Hold 26260.21 152718.98 178979.19 #> Resolved 28550.59 24078.61 53815.72 44273.36 150718.28 #> Shipped 572273.58 173511.94 100000.67 224078.56 195545.67 329581.91 1067131.83 220472.09 57756.43 374674.31 188167.81 307463.7 94015.73 288488.41 1044905.31 135043.08 117713.56 428472.21 3372204.28 9291501.08 #> Total 630623.1 202062.53 108412.62 224078.56 245637.15 329581.91 1110916.52 220472.09 57756.43 374674.31 188167.81 307463.7 94015.73 288488.41 1215686.92 210014.21 117713.56 478880.46 3627982.83 10032628.85