edamame 0.21

Exploratory data analysis tools

Installation

To install the package,

pip install edamame

the edamame package works correctly inside a .ipynb file.

import edamame as eda

Why Edamame?

Edamame is born under the inspiration of the pandas-profiling and pycaret packages. The scope of edamame is to build friendly and helpful functions for handling the EDA (exploratory data analysis) step in a dataset studied and after that train and analyze a models battery for regression or classification problems.

Exploratory data analysis functions

You can find an example of the EDA that uses the edamame package in the eda_example.ipynb notebook.

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.

Missing data

eda.missing(data)

TODO

• Finishing the documentation
• Add the xgboost model, PCA regression and other methods for studying the goodness of fit of the other models
• Add the classification part to the package