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Easily move row names to a column and vice-versa without the unwanted side-effects to object class and attributes. Drop-in replacement for tibble::rownames_to_column() and tibble::column_to_rownames() which can have undesired side-effects to complex object attributes. Does not import any external packages, modify the environment, or change the object (other than the desired column). When using col2rn(), if explicit row names exist, they are overwritten with a warning. add_rowid() does not affect row names, which differs from tibble::rowid_to_column().

Usage

rn2col(data, name = ".rn")

col2rn(data, name = ".rn")

has_rn(data)

rm_rn(data)

set_rn(data, value)

add_rowid(data, name = ".rowid")

Arguments

data

An object that inherits from class data.frame. Typically a soma_adat class object.

name

Character. The name of the column to move.

value

Character. The new set of names for the data frame. If duplicates exist they are modified on-the-fly via make.unique().

Value

All functions attempt to return an object of the same class as the input with fully intact and unmodified attributes (aside from those required by the desired action). has_rn() returns a scalar logical.

Functions

  • rn2col(): moves the row names of data to an explicit column whether they are explicit or implicit.

  • col2rn(): is the inverse of rn2col(). If row names exist, they will be overwritten (with warning).

  • has_rn(): returns a boolean indicating whether the data frame has explicit row names assigned.

  • rm_rn(): removes existing row names, leaving only "implicit" row names.

  • set_rn(): sets (and overwrites) existing row names for data frames only.

  • add_rowid(): adds a sequential integer row identifier; starting at 1:nrow(data). It does not remove existing row names currently, but may in the future (please code accordingly).

Examples

df <- data.frame(a = 1:5, b = rnorm(5), row.names = LETTERS[1:5])
df
#>   a          b
#> A 1  2.0650249
#> B 2 -1.6309894
#> C 3  0.5124269
#> D 4 -1.8630115
#> E 5 -0.5220125
rn2col(df)              # default name is `.rn`
#>   .rn a          b
#> 1   A 1  2.0650249
#> 2   B 2 -1.6309894
#> 3   C 3  0.5124269
#> 4   D 4 -1.8630115
#> 5   E 5 -0.5220125
rn2col(df, "AptName")   # pass `name =`
#>   AptName a          b
#> 1       A 1  2.0650249
#> 2       B 2 -1.6309894
#> 3       C 3  0.5124269
#> 4       D 4 -1.8630115
#> 5       E 5 -0.5220125

# moving columns
df$mtcars <- sample(names(mtcars), 5)
col2rn(df, "mtcars")   # with a warning
#> Warning: `df` already has row names. They will be over-written.
#>      a          b
#> cyl  1  2.0650249
#> disp 2 -1.6309894
#> am   3  0.5124269
#> wt   4 -1.8630115
#> gear 5 -0.5220125

# Move back and forth easily
# Leaves original object un-modified
identical(df, col2rn(rn2col(df)))
#> [1] TRUE

# add "id" column
add_rowid(mtcars)
#>                     .rowid  mpg cyl  disp  hp drat    wt  qsec vs am gear
#> Mazda RX4                1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4
#> Mazda RX4 Wag            2 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4
#> Datsun 710               3 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4
#> Hornet 4 Drive           4 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3
#> Hornet Sportabout        5 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3
#> Valiant                  6 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3
#> Duster 360               7 14.3   8 360.0 245 3.21 3.570 15.84  0  0    3
#> Merc 240D                8 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4
#> Merc 230                 9 22.8   4 140.8  95 3.92 3.150 22.90  1  0    4
#> Merc 280                10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4
#> Merc 280C               11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4
#> Merc 450SE              12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3
#> Merc 450SL              13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3
#> Merc 450SLC             14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3
#> Cadillac Fleetwood      15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3
#> Lincoln Continental     16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3
#> Chrysler Imperial       17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3
#> Fiat 128                18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4
#> Honda Civic             19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4
#> Toyota Corolla          20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4
#> Toyota Corona           21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3
#> Dodge Challenger        22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3
#> AMC Javelin             23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3
#> Camaro Z28              24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3
#> Pontiac Firebird        25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3
#> Fiat X1-9               26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4
#> Porsche 914-2           27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5
#> Lotus Europa            28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5
#> Ford Pantera L          29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5
#> Ferrari Dino            30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5
#> Maserati Bora           31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5
#> Volvo 142E              32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4
#>                     carb
#> Mazda RX4              4
#> Mazda RX4 Wag          4
#> Datsun 710             1
#> Hornet 4 Drive         1
#> Hornet Sportabout      2
#> Valiant                1
#> Duster 360             4
#> Merc 240D              2
#> Merc 230               2
#> Merc 280               4
#> Merc 280C              4
#> Merc 450SE             3
#> Merc 450SL             3
#> Merc 450SLC            3
#> Cadillac Fleetwood     4
#> Lincoln Continental    4
#> Chrysler Imperial      4
#> Fiat 128               1
#> Honda Civic            2
#> Toyota Corolla         1
#> Toyota Corona          1
#> Dodge Challenger       2
#> AMC Javelin            2
#> Camaro Z28             4
#> Pontiac Firebird       2
#> Fiat X1-9              1
#> Porsche 914-2          2
#> Lotus Europa           2
#> Ford Pantera L         4
#> Ferrari Dino           6
#> Maserati Bora          8
#> Volvo 142E             2

# remove row names
has_rn(mtcars)
#> [1] TRUE
mtcars2 <- rm_rn(mtcars)
has_rn(mtcars2)
#> [1] FALSE