Tiny Data Analysis Library
Project description
📈 Ickle - Data Analysis Library
A tiny DataFrame, statistics and analysis library for Python
Installation
Ickle can be installed via pip through PyPi
pip install ickle
Features
- DataFrame along with Visual Representation
- Basic properties (len, columns, shape, etc)
- Subset Selection
- Basic Methods (head, tail)
- Aggregation Methods (min, max, median, sum, etc)
- Non-Aggregation Methods (abs, copy, clip, cummin, etc)
- Additional Methods (isna, count, unique, etc)
- String-Only Methods (capitalize, center, count, find, etc)
- Pivot Table
- CSV
- read_csv
- to_csv
- Excel
- read_excel
- to_excel
... and more. 🚀 Checkout PATH.md to see the roadmap.
How To Contribute?
See 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.
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
Project details
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