Convert summary to data.frame

by

You can consider unclass, I suppose:

data.frame(unclass(summary(mydf)), check.names = FALSE, stringsAsFactors = FALSE)
#              ADMIT             GRE             GPA            RANK
# 1 Min.   :0.0000   Min.   :380.0   Min.   :2.930   Min.   :1.000  
# 2 1st Qu.:0.2500   1st Qu.:550.0   1st Qu.:3.047   1st Qu.:2.250  
# 3 Median :1.0000   Median :650.0   Median :3.400   Median :3.000  
# 4 Mean   :0.6667   Mean   :626.7   Mean   :3.400   Mean   :2.833  
# 5 3rd Qu.:1.0000   3rd Qu.:735.0   3rd Qu.:3.655   3rd Qu.:3.750  
# 6 Max.   :1.0000   Max.   :800.0   Max.   :4.000   Max.   :4.000  
str(.Last.value)
# 'data.frame': 6 obs. of  4 variables:
#  $     ADMIT: chr  "Min.   :0.0000  " "1st Qu.:0.2500  " "Median :1.0000  " "Mean   :0.6667  " ...
#  $      GRE : chr  "Min.   :380.0  " "1st Qu.:550.0  " "Median :650.0  " "Mean   :626.7  " ...
#  $      GPA : chr  "Min.   :2.930  " "1st Qu.:3.047  " "Median :3.400  " "Mean   :3.400  " ...
#  $      RANK: chr  "Min.   :1.000  " "1st Qu.:2.250  " "Median :3.000  " "Mean   :2.833  " ...

Note that there is a lot of excessive whitespace there, in both the names and the values.

However, it might be sufficient to do something like:

do.call(cbind, lapply(mydf, summary))
#          ADMIT   GRE   GPA  RANK
# Min.    0.0000 380.0 2.930 1.000
# 1st Qu. 0.2500 550.0 3.048 2.250
# Median  1.0000 650.0 3.400 3.000
# Mean    0.6667 626.7 3.400 2.833
# 3rd Qu. 1.0000 735.0 3.655 3.750
# Max.    1.0000 800.0 4.000 4.000

More Related Contents:

  1. Select the row with the maximum value in each group
  2. Replace values in a dataframe based on lookup table
  3. Sample random rows in dataframe
  4. Find indices of duplicated rows [duplicate]
  5. How to drop columns by name in a data frame
  6. Subset / filter rows in a data frame based on a condition in a column
  7. Replacing character values with NA in a data frame
  8. Coerce multiple columns to factors at once
  9. Reshape multiple values at once
  10. Remove columns from dataframe where ALL values are NA
  11. Delete rows that exist in another data frame? [duplicate]
  12. combining two data frames of different lengths [closed]
  13. Detect at least one match between each data frame row and values in vector
  14. Converting nested list to dataframe
  15. Cartesian product data frame
  16. Merge Two Lists in R
  17. Comparing two vectors in an if statement
  18. Randomly insert NAs into dataframe proportionaly
  19. How to delete rows where all the columns are zero
  20. Convert a dataframe to a vector (by rows)
  21. R: Split unbalanced list in data.frame column
  22. Transposing a dataframe maintaining the first column as heading
  23. Filter data frame rows based on values in vector
  24. Replace empty values with value from other column in a dataframe
  25. Replace values in data frame based on other data frame in R
  26. Add an image to a table-like output in R
  27. Convert a data frame to a data.table without copy
  28. Shifting a column down by one
  29. Identifying where value changes in R data.frame column
  30. What is the first column in R’s mtcars dataset?

Leave a Comment