Metadata-Version: 2.2
Name: dataidea
Version: 0.1.15
Summary: Learn Programming For Data Science
Home-page: https://github.com/dataidea/dataidea
Author: jumashafara
Author-email: jumashafara0@gmail.com
License: Apache Software License 2.0
Keywords: nbdev,jupyter,jupyter notebook,python,dataidea,machine learning,data,data science,science
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: plotly
Requires-Dist: yt-dlp
Requires-Dist: requests
Requires-Dist: python-dotenv
Provides-Extra: dev
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: provides-extra
Dynamic: requires-dist
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Dynamic: summary

## DATAIDEA Quickstart

### What is the `dataidea` package?

This is a package we are currently developing to help new and old data analysists walk around some repetitive and sometimes disturbing tasks that a data analyst does day to day

This library currently extends and depends on majorly numpy, pandas as sklearn and these, among a few others will be installed once you install dataidea

## Installing `dataidea`

- To install dataidea, you must have python installed on your machine
- It's advised that you install it in a virtual environment
- You can install `dataidea` using the command below

```python
pip install dataidea
```

### Learning `dataidea`

The best way to get started with dataidea (and data analysis) is to complete the free course.

To see what’s possible with dataidea, take a look at the Quick Start

Read through the [Tutorials](https://docs.dataidea.org) to learn how to load datasets, train your own models on your own datasets. Use the navigation to look through the dataidea documentation. Every class, function, and method is documented.

Link to the DATAIDEA documentation: [https://docs.dataidea.org](https://docs.dataidea.org)
