https://github.com/amhsirak/ickle

DataFrame, analysis & manipulation library for tiny labeled datasets
https://github.com/amhsirak/ickle

data-analysis dataframe datascience ickle pandas python

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DataFrame, analysis & manipulation library for tiny labeled datasets

• Host: GitHub
• URL: https://github.com/amhsirak/ickle
• Owner: amhsirak
• License: mit
• Created: 2021-11-24T13:20:34.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2024-01-31T18:23:24.000Z (10 months ago)
• Last Synced: 2024-11-11T18:37:34.906Z (6 days ago)
• Topics: data-analysis, dataframe, datascience, ickle, pandas, python
• Language: Jupyter Notebook
• Homepage: https://pypi.org/project/ickle/
• Size: 151 KB
• Stars: 14
• Watchers: 1
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
 📈 Ickle - Data Analysis Library




  A tiny DataFrame, statistics and analysis library for Python





[![PyPI version](https://badge.fury.io/py/ickle.svg)](https://badge.fury.io/py/ickle)

[![Downloads](https://static.pepy.tech/personalized-badge/ickle?period=total&units=international_system&left_color=grey&right_color=orange&left_text=Downloads)](https://pepy.tech/project/ickle)

[![Package Status](https://img.shields.io/static/v1?label=status&message=stable&color=brightgreen)](https://pypi.org/project/ickle/)

  



## Installation

Ickle can be installed via pip through PyPi

```

pip install ickle

```

## Features

- [x]  DataFrame along with Visual Representation

- [x]  Basic properties (len, columns, shape, etc)

- [x]  Subset Selection

- [x]  Basic Methods (head, tail)

- [x]  Aggregation Methods (min, max, median, sum, etc)

- [x]  Non-Aggregation Methods (abs, copy, clip, cummin, etc)

- [x]  Additional Methods (isna, count, unique, etc)

- [x]  String-Only Methods (capitalize, center, count, find, etc)

- [x]  Pivot Table

- [ ]  CSV

    - [x]  read_csv

    - [ ]  to_csv

- [ ]  Excel

    - [x]  read_excel

    - [ ]  to_excel

    

... and more. 🚀 Checkout [PATH.md](PATH.md) to see the roadmap.

## How To Contribute?

See [CONTRIBUTION.md](CONTRIBUTION.md) to know more.

## Getting Started

### DataFrame

A DataFrame holds two dimensional heterogenous data. It accepts dictionary as input, with Numpy arrays as values and strings as column names.

```py

import numpy as np

import ickle as ick

name = np.array(['John', 'Sam', 'Tina', 'Josh', 'Jack', 'Jill'])

place = np.array(['Kolkata', 'Mumbai', 'Delhi', 'Mumbai', 'Mumbai', 'Mumbai'])

weight = np.array([57, 70, 54, 59, 62, 70])

married = np.array([True, False, True, False, False, False])

data = {'name': name, 'place': place, 'weight': weight, 'married': married}

df = ick.DataFrame(data)

```

## Documentation

Read the documentation here

## Authors

@karishmashuklaa

@psy-pri