While a tibble can have row names (e.g., when converting from a regular data frame), they are removed when subsetting with the [ operator. A warning will be raised when attempting to assign non-NULL row names to a tibble. Generally, it is best to avoid row names, because they are basically a character column with different semantics to every other column. These functions allow to you detect if a data frame has row names (has_rownames()), remove them (remove_rownames()), or convert them back-and-forth between an explicit column (rownames_to_column() and column_to_rownames()). Also included is rowid_to_column() which adds a column at the start of the dataframe of ascending sequential row ids starting at 1. Note that this will remove any existing row names.

has_rownames(df)

remove_rownames(df)

rownames_to_column(df, var = "rowname")

rowid_to_column(df, var = "rowid")

column_to_rownames(df, var = "rowname")

Arguments

df

A data frame

var

Name of column to use for rownames.

Details

In the printed output, the presence of row names is indicated by a star just above the row numbers.

Examples

has_rownames(mtcars)
#> [1] TRUE
has_rownames(iris)
#> [1] FALSE
has_rownames(remove_rownames(mtcars))
#> [1] FALSE
head(rownames_to_column(mtcars))
#> rowname mpg cyl disp hp drat wt qsec vs am gear carb #> 1 Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 #> 2 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 #> 3 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 #> 4 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 #> 5 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 #> 6 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
mtcars_tbl <- as_tibble(rownames_to_column(mtcars)) mtcars_tbl
#> # A tibble: 32 x 12 #> rowname mpg cyl disp hp drat wt qsec vs am gear carb #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 Mazda RX4 21.0 6.00 160 110 3.90 2.62 16.5 0 1.00 4.00 4.00 #> 2 Mazda RX4… 21.0 6.00 160 110 3.90 2.88 17.0 0 1.00 4.00 4.00 #> 3 Datsun 710 22.8 4.00 108 93.0 3.85 2.32 18.6 1.00 1.00 4.00 1.00 #> 4 Hornet 4 … 21.4 6.00 258 110 3.08 3.22 19.4 1.00 0 3.00 1.00 #> 5 Hornet Sp… 18.7 8.00 360 175 3.15 3.44 17.0 0 0 3.00 2.00 #> 6 Valiant 18.1 6.00 225 105 2.76 3.46 20.2 1.00 0 3.00 1.00 #> 7 Duster 360 14.3 8.00 360 245 3.21 3.57 15.8 0 0 3.00 4.00 #> 8 Merc 240D 24.4 4.00 147 62.0 3.69 3.19 20.0 1.00 0 4.00 2.00 #> 9 Merc 230 22.8 4.00 141 95.0 3.92 3.15 22.9 1.00 0 4.00 2.00 #> 10 Merc 280 19.2 6.00 168 123 3.92 3.44 18.3 1.00 0 4.00 4.00 #> # ... with 22 more rows
column_to_rownames(as.data.frame(mtcars_tbl))
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> [ reached getOption("max.print") -- omitted 23 rows ]