Separate a data frame column into multiple columns-tidyr Part3

Separate a data frame column into multiple columns, To divide a data frame column into numerous columns, use the separate() function from the tidyr package.

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The basic syntax used by this function is as follows.

separate(data, col, into, sep)

where:

data: Name of the data frame

col: Name of the column to separate

into: a list of names to divide the column into

sep: The amount to use as a column separator is

Separate a data frame column into multiple columns

The practical application of this function is demonstrated in the examples that follow.

Example 1: Dividing a column into two

Let’s say we have the R data frame shown below.

Let’s create a data frame

df <- data.frame(player=c('P1', 'P1', 'P2', 'P2', 'P3', 'P3'),
year=c(1, 2, 1, 2, 1, 2),
stats=c('25-2', '22-3', '28-5', '21-9', '22-5', '29-3'))

Now we can view the data frame

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df

   player year stats
1     P1    1  25-2
2     P1    2  22-3
3     P2    1  28-5
4     P2    2  21-9
5     P3    1  22-5
6     P3    2  29-3

The stats column can be divided into two new columns labelled “points” and “assists” using the separate() function as follows:

library(tidyr)

divide the stats column into columns for points and assists.

separate(df, col=stats, into=c('points', 'assists'), sep='-')

   player year points assists
1     P1    1     25       2
2     P1    2     22       3
3     P2    1     28       5
4     P2    2     21       9
5     P3    1     22       5
6     P3    2     29       3

Example 2: Column Should Be Divided Into More Than Two Columns

The stats column can be divided into three distinct columns using the separate() function as follows.

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library(tidyr)

df <- data.frame(player=c('P1', 'P1', 'P2', 'P2', 'P3', 'P3'),
year=c(1, 2, 1, 2, 1, 2),
stats=c('25-2-3', '22-3-3', '28-5-3', '21-9-2', '22-5-1', '29-3-0'))

df

player year  stats
1     P1    1 25-2-3
2     P1    2 22-3-3
3     P2    1 28-5-3
4     P2    2 21-9-2
5     P3    1 22-5-1
6     P3    2 29-3-0

Stats column is split into three new columns.

separate(df, col=stats, into=c('points', 'assists', 'steals'), sep='-')

player year points assists steals
1     P1    1     25       2      3
2     P1    2     22       3      3
3     P2    1     28       5      3
4     P2    2     21       9      2
5     P3    1     22       5      1
6     P3    2     29       3      0

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