Emulate split() with dplyr group_by: return a list of data frames

by

group_split in dplyr:

Dplyr has implemented group_split:
https://dplyr.tidyverse.org/reference/group_split.html

It splits a dataframe by a groups, returns a list of dataframes. Each of these dataframes are subsets of the original dataframes defined by categories of the splitting variable.

For example. Split the dataset iris by the variable Species, and calculate summaries of each sub-dataset:

> iris %>% 
+     group_split(Species) %>% 
+     map(summary)
[[1]]
  Sepal.Length    Sepal.Width     Petal.Length    Petal.Width          Species  
 Min.   :4.300   Min.   :2.300   Min.   :1.000   Min.   :0.100   setosa    :50  
 1st Qu.:4.800   1st Qu.:3.200   1st Qu.:1.400   1st Qu.:0.200   versicolor: 0  
 Median :5.000   Median :3.400   Median :1.500   Median :0.200   virginica : 0  
 Mean   :5.006   Mean   :3.428   Mean   :1.462   Mean   :0.246                  
 3rd Qu.:5.200   3rd Qu.:3.675   3rd Qu.:1.575   3rd Qu.:0.300                  
 Max.   :5.800   Max.   :4.400   Max.   :1.900   Max.   :0.600                  

[[2]]
  Sepal.Length    Sepal.Width     Petal.Length   Petal.Width          Species  
 Min.   :4.900   Min.   :2.000   Min.   :3.00   Min.   :1.000   setosa    : 0  
 1st Qu.:5.600   1st Qu.:2.525   1st Qu.:4.00   1st Qu.:1.200   versicolor:50  
 Median :5.900   Median :2.800   Median :4.35   Median :1.300   virginica : 0  
 Mean   :5.936   Mean   :2.770   Mean   :4.26   Mean   :1.326                  
 3rd Qu.:6.300   3rd Qu.:3.000   3rd Qu.:4.60   3rd Qu.:1.500                  
 Max.   :7.000   Max.   :3.400   Max.   :5.10   Max.   :1.800                  

[[3]]
  Sepal.Length    Sepal.Width     Petal.Length    Petal.Width          Species  
 Min.   :4.900   Min.   :2.200   Min.   :4.500   Min.   :1.400   setosa    : 0  
 1st Qu.:6.225   1st Qu.:2.800   1st Qu.:5.100   1st Qu.:1.800   versicolor: 0  
 Median :6.500   Median :3.000   Median :5.550   Median :2.000   virginica :50  
 Mean   :6.588   Mean   :2.974   Mean   :5.552   Mean   :2.026                  
 3rd Qu.:6.900   3rd Qu.:3.175   3rd Qu.:5.875   3rd Qu.:2.300                  
 Max.   :7.900   Max.   :3.800   Max.   :6.900   Max.   :2.500

It is also very helpful for debugging a calculations on nested dataframes, because it is an quick way to “see” what is going on “inside” the calculations on nested dataframes.

More Related Contents:

  1. Apply a ggplot-function per group with dplyr and set title per group
  2. Convert a list to a data frame
  3. Relative frequencies / proportions with dplyr
  4. Split string column to create new binary columns
  5. Unique rows, considering two columns, in R, without order
  6. standard evaluation in dplyr: summarise a variable given as a character string
  7. Use variable names in functions of dplyr
  8. do.call(rbind, list) for uneven number of column
  9. Finding percentage in a sub-group using group_by and summarise
  10. Make a group_indices based on several columns
  11. How to correctly use lists?
  12. Using spread with duplicate identifiers for rows
  13. dplyr filter with condition on multiple columns
  14. dplyr – using column names as function arguments
  15. Append value to empty vector in R?
  16. Fill missing dates by group
  17. dplyr – filter by group size
  18. dplyr::group_by_ with character string input of several variable names
  19. How to parametrize function calls in dplyr 0.7?
  20. Select first element of nested list
  21. How to filter rows based on difference in dates between rows in R?
  22. Delete a column in a data frame within a list
  23. How to do range grouping on a column using dplyr?
  24. Split Data Frame into Rows of Fixed Size
  25. R sum a variable by two groups [duplicate]
  26. data.table row-wise sum, mean, min, max like dplyr?
  27. Update/Replace Values in Dataframe with Tidyverse Join
  28. Split a string every 5 characters
  29. Duplicate list names in R
  30. Collapse all columns by an ID column [duplicate]

Leave a Comment