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Aggregating multiple columns in R refers to the process of combining or summarizing data from different columns into a single column. This can be useful for analyzing and understanding patterns or trends in large datasets. One way to aggregate columns in R is by using the aggregate() function, which allows for the creation of new columns based on the values in existing columns. For example, if we have a dataset with columns for sales by month and by product, we can use the aggregate() function to calculate the total sales for each product over the entire year. Other functions such as sum(), mean(), and count() can also be used for aggregation purposes. Overall, aggregating multiple columns in R can help simplify and streamline data analysis and provide valuable insights.
Aggregate Multiple Columns in R (With Examples)
We can use the aggregate() function in R to produce summary statistics for one or more variables in a data frame.
This function uses the following basic syntax:
aggregate(sum_var ~ group_var, data = df, FUN = mean)
where:
- sum_var: The variable to summarize
- group_var: The variable to group by
- data: The name of the data frame
- FUN: The summary statistic to compute
This tutorial provides several examples of how to use this function to aggregate one or more columns at once in R, using the following data frame as an example:
#create data frame df <- data.frame(team=c('A', 'A', 'A', 'B', 'B', 'B', 'C', 'C'), conf=c('E', 'E', 'W', 'W', 'W', 'W', 'W', 'W'), points=c(1, 3, 3, 4, 5, 7, 7, 9), rebounds=c(7, 7, 8, 3, 2, 7, 14, 13)) #view data frame df team conf points rebounds 1 A E 1 7 2 A E 3 7 3 A W 3 8 4 B W 4 3 5 B W 5 2 6 B W 7 7 7 C W 7 14 8 C W 9 13
Example 1: Summarize One Variable & Group by One Variable
The following code shows how to find the mean points scored, grouped by team:
#find mean points scored, grouped by team aggregate(points ~ team, data = df, FUN = mean, na.rm = TRUE) team points 1 A 2.333333 2 B 5.333333 3 C 8.000000
Example 2: Summarize One Variable & Group by Multiple Variables
The following code shows how to find the mean points scored, grouped by team and conference:
#find mean points scored, grouped by team and conference aggregate(points ~ team + conf, data = df, FUN = mean, na.rm = TRUE) team conf points 1 A E 2.000000 2 A W 3.000000 3 B W 5.333333 4 C W 8.000000
Example 3: Summarize Multiple Variables & Group by One Variable
The following code shows how to find the mean points and the mean rebounds, grouped by team:
#find mean points scored, grouped by team and conference aggregate(cbind(points,rebounds) ~ team, data = df, FUN = mean, na.rm = TRUE) team points rebounds 1 A 2.333333 7.333333 2 B 5.333333 4.000000 3 C 8.000000 13.500000
Example 4: Summarize Multiple Variables & Group by Multiple Variables
#find mean points scored, grouped by team and conference aggregate(cbind(points,rebounds) ~ team + conf, data = df, FUN = mean, na.rm = TRUE) team conf points rebounds 1 A E 2.000000 7.0 2 A W 3.000000 8.0 3 B W 5.333333 4.0 4 C W 8.000000 13.5