How can I use dcast Function from data.table in R?

The dcast function from the data.table package in R is a convenient and powerful tool for reshaping data. It can be used to transform a data frame from a wide to a long format, or from a long to a wide format, while preserving the values of the data. It is also a useful tool for aggregating data, as it can be used to calculate summary statistics such as means, medians, and counts. It is very flexible and can be used to reshape data for many different applications.


You can use the dcast function from the data.table package in R to reshape a data frame from a to a wide format.

This function is particularly useful when you want to summarize specific variables in a data frame, grouped by other variables.

The following examples show how to use the dcast function in practice with the following data frame in R:

library(data.table)

#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
                 position=c('G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'),
                 points=c(18, 13, 10, 12, 16, 25, 24, 31),
                 assists=c(9, 8, 8, 5, 12, 15, 10, 7))

#convert data frame to data table
dt <- setDT(df)

#view data table
dt

   team position points assists
1:    A        G     18       9
2:    A        G     13       8
3:    A        F     10       8
4:    A        F     12       5
5:    B        G     16      12
6:    B        G     25      15
7:    B        F     24      10
8:    B        F     31       7

Example 1: Calculate Metric for One Variable, Grouped by Other Variables

The following code shows how to use the dcast function to calculate the mean points value, grouped by the team and position variables:

library(data.table)

#calculate mean points value by team and position
dt_new <- dcast(dt,
                team + position ~ .,
                fun.aggregate = mean, 
                value.var = 'points')

#view results
dt_new

   team position    .
1:    A        F 11.0
2:    A        G 15.5
3:    B        F 27.5
4:    B        G 20.5

Example 2: Calculate Multiple Metrics for One Variable, Grouped by Other Variables

The following code shows how to use the dcast function to calculate the mean points value and the max points value, grouped by the team and position variables:

library(data.table)

#calculate mean and max points values by team and position
dt_new <- dcast(dt,
                team + position ~ .,
                fun.aggregate = list(mean, max), 
                value.var = 'points')

#view results
dt_new

   team position points_mean points_max
1:    A        F        11.0         12
2:    A        G        15.5         18
3:    B        F        27.5         31
4:    B        G        20.5         25

Example 3: Calculate Metric for Multiple Variables, Grouped by Other Variables

The following code shows how to use the dcast function to calculate the mean points value and mean assists value, grouped by the team and position variables:

library(data.table)

#calculate mean and max points values by team and position
dt_new <- dcast(dt,
                team + position ~ .,
                fun.aggregate = mean, 
                value.var = c('points', 'assists'))

#view results
dt_new

   team position points assists
1:    A        F   11.0     6.5
2:    A        G   15.5     8.5
3:    B        F   27.5     8.5
4:    B        G   20.5    13.5

The following tutorials provide additional information about data tables:

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