Auxiliary functions to clean pandas data frames
Project description
Pywrangle
Library with auxiliary functions to clean pandas data frames. Available on PyPI here
Install
- Python 3.6+
- numpy
- pandas
To install pywrangle, use pip:
pip install pywrangle
Import
Per convention with Python Analysis modules, import pywrangle as follows:
>>> import pywrangle as pw
Missing Data
print_nulls_per_col(df) -> None: Calculates number of null values in each column and prints result.
String cleaning
def clean_str_columns(df: object, col_strcase_tuple: tuple) -> df: Master function to clean string columns using col_strcase_tuple key.
TODO:
TODO lists available in pywrangle functions.
- Add testing documenation.
- Missing data functions
- show correlation between NULL values in different columns. e.g., if state is missing, likely region is missing too
- barchart with number of NULL per num columns
- show number of rows with NULL in only 1 column, 2 columns, 3 columns etc.
- May like to include optional parameters to show correlation b/w NULL values in different columns?
- Print number of rows with NULL in X columns - optional param for desc sort by num NULL?
- Create wrapper that prints changes in the data frame size.
- Helpful when dropping is_na rows.
- Can create optional param to assert that dropped_rows = num_na before
- Create pywrangle documentation website?
Project details
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