Metadata-Version: 2.1
Name: qdesc
Version: 0.1.2
Summary: Quick and Easy way to do descriptive analysis.
Author: Paolo Hilado
Author-email: datasciencepgh@proton.me
Description-Content-Type: text/markdown
License-File: LICENCE.txt

# qdesc - Quick and Easy Descriptive Analysis

## Overview
This is a package for quick and easy descriptive analysis.
Required packages include: pandas, numpy, and SciPy version 1.14.1
Be sure to run the following prior to using the "qd.desc" function:

- import pandas as pd
- import numpy as np
- from scipy.stats import anderson
- import qdesc as qd

The qdesc package provides a quick and easy approach to do descriptive analysis for quantitative data.

Run the function qd.desc(df) to get the following statistics:
* count - number of observations
* mean - measure of central tendency for normal distribution	
* std - measure of spread for normal distribution
* median - measure of central tendency for skewed distributions or those with outliers
* MAD - measure of spread for skewed distributions or those with outliers; this is manual Median Absolute Deviation (MAD) which is more robust when dealing with non-normal distributions.
* min - lowest observed value
* max - highest observed value	
* AD_stat	- Anderson - Darling Statistic
* 5% crit_value - critical value for a 5% Significance Level	
* 1% crit_value - critical value for a 1% Significance Level

Run the function qd.freqdist(df, "Variable Name") to easily create a frequency distribution for your chosen categorical variable with the following:
* Variable Levels (i.e., for Sex Variable: Male and Female)
* Counts - the number of observations
* Percentage - percentage of observations from total.

Later versions will include data visualizations handy for exploring the distribution of the data set.

## Installation
pip install qdesc

## Usage - doing descriptive analysis using qdesc
### import qdesc as qd
### qd.desc(df)

## License
This project is licensed under the GPL-3 License. See the LICENSE file for more details.

## Acknowledgements
Acknowledgement of the libraries used by this package...

### Pandas
Pandas is distributed under the BSD 3-Clause License, pandas is developed by Pandas contributors. Copyright (c) 2008-2024, the pandas development team All rights reserved.
### NumPy
NumPy is distributed under the BSD 3-Clause License, numpy is developed by NumPy contributors. Copyright (c) 2005-2024, NumPy Developers. All rights reserved.
### SciPy
SciPy is distributed under the BSD License, scipy is developed by SciPy contributors. Copyright (c) 2001-2024, SciPy Developers. All rights reserved.





