Depivot a dataframe and retrieve unique counts for each column with the option of grouping the counts with a `grouper` column.
value_count( data, names_to = "Variable", values_to = "Value", desc = TRUE, grouper )
| data | A dataframe or tibble. |
|---|---|
| names_to | Passed to `tidyr::pivot_longer()`. |
| values_to | Passed to `tidyr::pivot_longer()`. |
| desc | If TRUE, the output is arranged in descending order. Otherwise it is arranged in ascending order. |
| grouper | (Optional) Group by column. |
pivot_longer
reexports,count,tidyeval-compat,arrange
Other summarize functions:
summarize_max()
library(tidyverse) test_data <- tibble( Group = sample(c("Apple", "Pear"), size = 10, replace = TRUE), A = sample(c(NA_integer_, 1:3), size = 10, replace = TRUE), B = sample(c(NA_integer_, 4:6), size = 10, replace = TRUE), C = sample(c(NA_real_, seq(from = 6.01, to = 6.09, by = 0.01)), size = 10, replace = TRUE) ) summarize_variables(data = test_data, incl_num_calc = FALSE)#> # A tibble: 4 x 7 #> Variable COUNT DISTINCT_COUNT NA_COUNT NA_STR_COUNT BLANK_COUNT #> <chr> <int> <int> <int> <int> <int> #> 1 A 10 4 2 0 0 #> 2 B 10 4 1 0 0 #> 3 C 10 8 1 0 0 #> 4 Group 10 2 0 0 0 #> # … with 1 more variable: DISTINCT_VALUES <chr>#> $SUMMARY #> # A tibble: 4 x 7 #> Variable COUNT DISTINCT_COUNT NA_COUNT NA_STR_COUNT BLANK_COUNT #> <chr> <int> <int> <int> <int> <int> #> 1 A 10 4 2 0 0 #> 2 B 10 4 1 0 0 #> 3 C 10 8 1 0 0 #> 4 Group 10 2 0 0 0 #> # … with 1 more variable: DISTINCT_VALUES <chr> #> #> $NUMERIC_CALCULATIONS #> # A tibble: 3 x 17 #> Variable MEAN MEAN_NA MEDIAN MEDIAN_NA SD SD_NA MAX MAX_NA MIN MIN_NA #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 A 1.75 NA 1.5 NA 0.886 NA 3 NA 1 NA #> 2 B 5.33 NA 6 NA 0.866 NA 6 NA 4 NA #> 3 C 6.05 NA 6.04 NA 0.0307 NA 6.09 NA 6.01 NA #> # … with 6 more variables: SUM <dbl>, SUM_NA <dbl>, DISTINCT_LENGTH <int>, #> # NA_LENGTH <int>, BLANK_LENGTH <int>, DISTINCT_STR <chr> #>#> $SUMMARY #> # A tibble: 6 x 8 #> # Groups: Group [2] #> Group Variable COUNT DISTINCT_COUNT NA_COUNT NA_STR_COUNT BLANK_COUNT #> <chr> <chr> <int> <int> <int> <int> <int> #> 1 Apple A 6 3 1 0 0 #> 2 Apple B 6 4 1 0 0 #> 3 Apple C 6 6 1 0 0 #> 4 Pear A 4 3 1 0 0 #> 5 Pear B 4 2 0 0 0 #> 6 Pear C 4 3 0 0 0 #> # … with 1 more variable: DISTINCT_VALUES <chr> #> #> $NUMERIC_CALCULATIONS #> # A tibble: 6 x 18 #> # Groups: Group [2] #> Group Variable MEAN MEAN_NA MEDIAN MEDIAN_NA SD SD_NA MAX MAX_NA #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 Apple A 1.2 NA 1 NA 0.447 NA 2 NA #> 2 Apple B 5.2 NA 5 NA 0.837 NA 6 NA #> 3 Apple C 6.06 NA 6.07 NA 0.0311 NA 6.09 NA #> 4 Pear A 2.67 NA 3 NA 0.577 NA 3 NA #> 5 Pear B 5.5 5.5 6 6 1 1 6 6 #> 6 Pear C 6.04 6.04 6.04 6.04 0.0332 0.0332 6.09 6.09 #> # … with 8 more variables: MIN <dbl>, MIN_NA <dbl>, SUM <dbl>, SUM_NA <dbl>, #> # DISTINCT_LENGTH <int>, NA_LENGTH <int>, BLANK_LENGTH <int>, #> # DISTINCT_STR <chr> #>#> # A tibble: 6 x 8 #> # Groups: Group [2] #> Group Variable COUNT DISTINCT_COUNT NA_COUNT NA_STR_COUNT BLANK_COUNT #> <chr> <chr> <int> <int> <int> <int> <int> #> 1 Apple A 6 3 1 0 0 #> 2 Apple B 6 4 1 0 0 #> 3 Apple C 6 6 1 0 0 #> 4 Pear A 4 3 1 0 0 #> 5 Pear B 4 2 0 0 0 #> 6 Pear C 4 3 0 0 0 #> # … with 1 more variable: DISTINCT_VALUES <chr>#> # A tibble: 10 x 5 #> Group A B C n #> <chr> <int> <int> <dbl> <int> #> 1 Apple 1 5 6.02 1 #> 2 Apple 1 6 6.08 1 #> 3 Apple 1 6 NA 1 #> 4 Apple 1 NA 6.07 1 #> 5 Apple 2 4 6.03 1 #> 6 Apple NA 5 6.09 1 #> 7 Pear 2 6 6.04 1 #> 8 Pear 3 4 6.04 1 #> 9 Pear 3 6 6.09 1 #> 10 Pear NA 6 6.01 1value_count(data = test_data)#> # A tibble: 18 x 3 #> Variable Value n #> <chr> <chr> <int> #> 1 Group Apple 6 #> 2 B 6 5 #> 3 A 1 4 #> 4 Group Pear 4 #> 5 A 2 2 #> 6 A 3 2 #> 7 A NA 2 #> 8 B 4 2 #> 9 B 5 2 #> 10 C 6.04 2 #> 11 C 6.09 2 #> 12 B NA 1 #> 13 C 6.01 1 #> 14 C 6.02 1 #> 15 C 6.03 1 #> 16 C 6.07 1 #> 17 C 6.08 1 #> 18 C NA 1value_count(data = test_data, grouper = Group)#> # A tibble: 21 x 4 #> Group Variable Value n #> <chr> <chr> <chr> <int> #> 1 Apple A 1 4 #> 2 Pear B 6 3 #> 3 Apple B 5 2 #> 4 Apple B 6 2 #> 5 Pear A 3 2 #> 6 Pear C 6.04 2 #> 7 Apple A 2 1 #> 8 Apple A NA 1 #> 9 Apple B 4 1 #> 10 Apple B NA 1 #> # … with 11 more rows