Replaces all numerical columns of a data frame with their ranks. Uses sport ranking, i.e. ties
share the highest rank place. Ignores non-numerical columns. See rank(). Optionally, returns in-group ranks
using a specified grouping column.
Arguments
- df
A data frame
- use_group
An optional column of df (specified as a string) to use as a grouping variable. If specified, returns ranks inside each group present in this column.
Value
A data frame equal to the data frame that was input, but with any numerical columns replaced with ranks.
Examples
# some random data, with a column of characters
df <- data.frame(RName = c("A", "B", "C"),
Score1 = runif(3), Score2 = runif(3))
# convert to ranks
rank_df(df)
#> RName Score1 Score2
#> 1 A 1 3
#> 2 B 3 2
#> 3 C 2 1
# grouped ranking - use some example data
df1 <- ASEM_iData[c("uCode", "GDP_group", "Goods", "LPI")]
rank_df(df1, use_group = "GDP_group")
#> uCode GDP_group Goods LPI
#> 1 AUT L 7 5
#> 2 BEL L 2 4
#> 3 BGR S 2 10
#> 4 HRV S 5 6
#> 5 CYP S 11 8
#> 6 CZE M 1 2
#> 7 DNK L 10 7
#> 8 EST S 7 3
#> 9 FIN M 7 1
#> 10 FRA XL 3 4
#> 11 DEU XL 1 1
#> 12 GRC M 8 7
#> 13 HUN M 3 3
#> 14 IRL L 12 8
#> 15 ITA XL 6 6
#> 16 LVA S 6 4
#> 17 LTU S 3 2
#> 18 LUX S 4 1
#> 19 MLT S 9 7
#> 20 NLD L 1 2
#> 21 NOR L 11 9
#> 22 POL L 5 11
#> 23 PRT M 6 4
#> 24 ROU M 5 8
#> 25 SVK M 4 6
#> 26 SVN S 1 5
#> 27 ESP XL 8 7
#> 28 SWE L 9 1
#> 29 CHE L 4 6
#> 30 GBR XL 4 2
#> 31 AUS XL 11 5
#> 32 BGD M 9 12
#> 33 BRN S 13 9
#> 34 KHM S 8 11
#> 35 CHN XL 2 9
#> 36 IND XL 10 10
#> 37 IDN XL 12 11
#> 38 JPN XL 5 3
#> 39 KAZ M 10 11
#> 40 KOR XL 7 8
#> 41 LAO S 10 13
#> 42 MYS L 8 10
#> 43 MNG S 12 12
#> 44 MMR M 13 13
#> 45 NZL M 11 5
#> 46 PAK M 12 10
#> 47 PHL L 13 13
#> 48 RUS XL 9 12
#> 49 SGP L 3 3
#> 50 THA L 6 12
#> 51 VNM M 2 9