Pandas-Data-Exploration-Utility-Package 0.0.3

Utility functions to help with exploratory data analysis on top the Pandas APIs

Pandas Data Exploration Utility Package

Table of content

• Overview
• Installation
• Usage
  • Visualization Module
    • Pareto plot
    • Distribution plot
    • X-Y plot
• Recommended development setup

Overview

Pandas Data Exploration utility is an interactive, notebook based library for quickly profiling and exploring the shape of data and the relationships between data. Using existing APIs from IpyWidget, Plot.ly, and Pandas, it creates a flexible point and click widget that allows the user to easily explore and visualize the dataset.
This is a work in progress, and I welcome any suggestions on features and/or enhancements.

Installation

pip install Pandas-Data-Exploration-Utility-Package

Usage

Visualization Module

import pandas as pd
import pandas_exploration_util.viz.explore as pe

global_temp = pd.read_csv("./data/GlobalTemperatures.csv", parse_dates = [0], infer_datetime_format=True)

pe.generate_widget(global_temp)

see /test for sample data and test jupyter notebook
https://github.com/yifeihuang/pandas_exploration_util/tree/master/test

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Pareto plot

Visualize the top values of any column as ranked by aggregation of any other column. Support aggregation functions include 'count', 'sum', 'mean', 'std', 'max', 'min', 'uniques'

Distribution plot

Visualize distribution of any numerical value. Binning is automatically determined by the plot.ly histogram method.

X-Y plot

Visualize the X-Y scatter of any column vs aggregation of any other column. Support aggregation functions include 'count', 'sum', 'mean', 'std', 'max', 'min', 'uniques'

Recommended development setup

Local Dev

1. Setup virtualenv
2. Create a virtual environment using virtualenv /path/to/env/dir
3. Activate virtual environment using source /path/to/env/dir/bin/activate
4. Clone the repo locally
5. Navigate the root directory of the repo where the setup.py lives
6. Install the module in development mode using python setup.py develop
7. Run the Jupyter notebook that is in the virtual environment directory, which should have installed as the part of the dependency of the module
8. Dev away
9. When done uninstall the package using python setup.py develop --uninstall
10. Deactive the environment using deactivate

Building and distributing

https://packaging.python.org/tutorials/packaging-projects/
Assuming all relevant tools are installed and the relevant project files are properly defined

1. build the distribution using python3 setup.py sdist bdist_wheel
2. upload the distribution using twine upload dist/*{version}*