Exploratory data analysis tools
Project description
Installation
To install the package,
pip install edamame
edamame functions work correctly inside a .ipynb file.
import edamame as eda
Exploratory data analysis functions
Dimensions
a prettier version of the .shape method
eda.dimensions(data)
the function displays the number of rows and columns of a pandas dataframe passed
Describe distribution
eda.describe_distribution(data)
passing a dataframe the function display the result of the .describe() method applied to a pandas dataframe, divided by quantitative/numerical and categorical/object columns.
Identify columns types
eda.identify_types(data)
passing a dataframe the function display the result of the .dtypes method and returns a list with the name of the quantitative/numerical columns and a list with the name of the columns identified as "object" by pandas.
Convert numerical columns to categorical
eda.identify_types(data, col: list[str])
passing a dataframe and a list with columns name, the function transforms the types of the columns into "object". This operation can help convert numerical columns we know to be categorical.
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