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The post How to Create a Frequency Table by Group in R? appeared first on Data Science Tutorials

How to Create a Frequency Table by Group in R?, To produce a frequency table by the group in R, use the dplyr package’s following functions.

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## How to Create a Frequency Table by Group in R

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

```df <- data.frame(team=c('P1', 'P1', 'P1', 'P2', 'P2', 'P3', 'P3', 'P3'),
position=c('R1', 'R3', 'R2', 'R2', 'R1', 'R1', 'R2', 'R1'))```

Now we can view the data frame

```df
team position
1   P1       R1
2   P1       R3
3   P1       R2
4   P2       R2
5   P2       R1
6   P3       R1
7   P3       R2
8   P3       R1```

Let’s say that we want to make a table of frequencies that lists the frequency of each position, sorted by team.

To do this, we can use the syntax shown below.

`library(dplyr)`

compute position frequency, grouped by team.

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```df %>%
group_by(team, position) %>%
summarize(Freq=n())
team  position  Freq
<chr> <chr>    <int>
1 P1    R1           1
2 P1    R2           1
3 P1    R3           1
4 P2    R1           1
5 P2    R2           1
6 P3    R1           2
7 P3    R2           1```

How to interpret the result is as follows:

1 player on team P1 has position ‘R1’

1 player on team P1 have position ‘R2’

And so on…

Keep in mind that by modifying the variable name in the summarise() method, we can rename the column that contains the frequencies.

We could, for instance, change the column’s name to “count” instead.

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`library(dplyr)`

compute position frequency, grouped by team.

```df %>%
group_by(team, position) %>%
summarize(count=n())
team  position count
<chr> <chr>    <int>
1 P1    R1           1
2 P1    R2           1
3 P1    R3           1
4 P2    R1           1
5 P2    R2           1
6 P3    R1           2
7 P3    R2           1```

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