Missing Data Explorer

Nelson Gonzabato


mde 0.2.1

mde version 0.2.0


  1. na_summary which provides a very quick overview of missingness. It also supports grouped summaries.

  2. drop_na_if allows easy dropping of columns where all values are missing.

  3. custom_na_recode allows replacing missing values with common values such as mean, min, max, sd.

Major changes

  1. In percent_missing, the argument grouped was dropped in favour of simply providing a grouping_cols vector.

  2. In recode_as_na , subset_df was dropped. It now simply accepts an optional subset_cols argument. The argument tidy was also dropped.One can simply provide an optional pattern_type and pattern.

  3. Similar changes were made for recode_na_as as above.

  4. The argument x was changed to df in drop_na_at.

mde version 0.1.0

Available functions

  1. get_na_counts

  2. percent_missing

  3. recode_as_na

  4. sort_by_missingness

  5. recode_na_as

  6. drop_na_if

  7. recode_na_if

  8. drop_na_at

  9. recode_as_na_for

Key changes

  1. Now supports tidy selection and exploration at specific columns

  2. percent_missing supports grouping and exclusion of certain columns. The use of decimals was dropped.

  3. drop_na_if allows exclusion of columns.