#108 Spilled data? Call the PyJanitor

• originally a port of an R package called janitor, now much more.
• “pyjanitor’s etymology has a two-fold relationship to “cleanliness”. Firstly, it’s about extending Pandas with convenient data cleaning routines. Secondly, it’s about providing a cleaner, method-chaining, verb-based API for common pandas routines.”
• functionality:
  • Cleaning columns name (multi-indexes are possible!)
  • Removing empty rows and columns
  • Identifying duplicate entries
  • Encoding columns as categorical
  • Splitting your data into features and targets (for machine learning)
  • Adding, removing, and renaming columns
  • Coalesce multiple columns into a single column
  • Convert excel date (serial format) into a Python datetime format
  • Expand a single column that has delimited, categorical values into dummy-encoded variables
• This pandas code:

    df = pd.DataFrame(...)  # create a pandas DataFrame somehow.
    del df['column1']  # delete a column from the dataframe.
    df = df.dropna(subset=['column2', 'column3'])  # drop rows that have empty values in column 2 and 3.
    df = df.rename({'column2': 'unicorns', 'column3': 'dragons'})  # rename column2 and column3
    df['newcolumn'] = ['iterable', 'of', 'items']  # add a new column.
- looks like this with pyjanitor:
    df = (
        pd.DataFrame(...)
        .remove_columns(['column1'])
        .dropna(subset=['column2', 'column3'])
        .rename_column('column2', 'unicorns')
        .rename_column('column3', 'dragons')
        .add_column('newcolumn', ['iterable', 'of', 'items'])
    )