tidyverse – prefered way to turn a named vector into a data.frame/tibble

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  1. combine two data frames with all posible combinations
  2. Spread with duplicate identifiers (using tidyverse and %>%) [duplicate]
  3. Replace values greater than zero with 1 in r
  4. Gather multiple sets of columns
  5. How to use Pivot_longer to reshape from wide-type data to long-type data with multiple variables
  6. Combine Multiple Columns Into Tidy Data [duplicate]
  7. R spreading multiple columns with tidyr [duplicate]
  8. dplyr summarise: Equivalent of “.drop=FALSE” to keep groups with zero length in output
  9. Using spread with duplicate identifiers for rows
  10. Proper idiom for adding zero count rows in tidyr/dplyr
  11. Add NAs to make all list elements equal length
  12. Reshape from long to wide and create columns with binary value
  13. How to use map from purrr with dplyr::mutate to create multiple new columns based on column pairs
  14. adding default values to item x group pairs that don’t have a value (df %>% spread %>% gather seems strange)
  15. Filling missing dates in a grouped time series – a tidyverse-way?
  16. data.table equivalent of tidyr::complete()
  17. Canonical tidyverse method to update some values of a vector from a look-up table
  18. Spreading a two column data frame with tidyr
  19. Error with select function from dplyr
  20. Mutate multiple variable to create multiple new variables
  21. How to replace all NA in a dataframe using tidyr::replace_na? [duplicate]
  22. mutate with case_when and contains
  23. Add row in each group using dplyr and add_row()
  24. pivot_longer into multiple columns
  25. loess regression on each group with dplyr::group_by()
  26. Unlisting columns by groups
  27. Adding column if it does not exist
  28. R – add column that counts sequentially within groups but repeats for duplicates
  29. Means multiple columns by multiple groups [duplicate]
  30. How to speed up subset by groups

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