Data Preprocessing Module

This python module preprocesses a csv dataset, which has a categorical data at the last column. This module makes use of scikit-learn, pandas and numpy.

The following steps of preprocessing be done in order:

1. Importing Dataset
2. Missing Value treatement
3. Encoding Categorical Data
4. Splitting Dataset into training and testing set
5. Feature Scaling using Standard Scaler

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Inut and output

• The input value to the sole function preprocess is a csv dataset

• The return value is a tuple of 4 values in the fashing of train_test_split of scikit-learn, i.e X_train, X_test, y_train, y_test**

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Module Installation from PyPI

$ pip install processdat

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Usage

> import processdat as pro

...
X_train, X_test, y_train, y_test = pro.preprocess('Data.csv')
...

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Developing processdat

To install processdat, along with the tools you need to develop and run tests, run the following in the terminal/environment:

$ pip install -e .[dev]

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Created by: Shayan Banerjee (shayanbanerhee96@gmail.com)