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‎README.md

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# Welcome to Visual Python
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![Visual Python](https://i.esdrop.com/d/7o0dj05m8rnz/JNGCMedl18.png)
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**Visual Python** is a GUI-based Python code generator for data science.
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**Visual Python** is an extension to Jupyter Notebook.
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[![PyPI version shields.io](https://img.shields.io/pypi/v/visualpython)](https://pypi.python.org/pypi/visualpython/)
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![Python: 3.x](https://img.shields.io/badge/Python-3.x-yellowgreen)
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[![License: GPLv3](https://img.shields.io/badge/License-GPLv3-brightgreen)](https://github.com/visualpython/visualpython/blob/main/LICENSE)
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[![Code of Conduct: Contributor Covenant](https://img.shields.io/badge/Code%20of%20Conduct-Contributor%20Covenant-pink)](https://github.com/visualpython/visualpython/blob/main/CODE_OF_CONDUCT.md)
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[![Downloads](https://static.pepy.tech/personalized-badge/visualpython?period=total&units=international_system&left_color=grey&right_color=orange&left_text=Downloads)](https://pepy.tech/project/visualpython)
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[![Issues: ](https://img.shields.io/github/issues/visualpython/visualpython?color=%23FF6347)](https://github.com/visualpython/visualpython/issues)
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**Visual Python** is an open source project started for students who struggle with coding during Python classes for data science.
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## Introduction
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Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook as an extension. <br>
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Visual Python is an open source project started for students who struggle with coding during Python classes for data science.
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![Visual Python v2.2.8 ](<.gitbook/assets/Visual Python\_2.2.8.gif>)
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<br>
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## Try Visual Python if you would like to
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Try Visual Python if you would like to: <br>
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* manage big data with minimal coding skills. <br>
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* help students / business analysts / researchers to overcome learning barriers for Python. <br>
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* save & reuse repeatedly used codes(snippets). <br>
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* manage big data with minimal coding skills.&#x20;
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* help students / business analysts / researchers to overcome learning barriers for Python.&#x20;
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* save & reuse repeatedly used codes(snippets).
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<br>
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<img src="https://github.com/visualpython/visualpython/blob/main/img/Visual%20Python_2.2.8.gif" width="85%">
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## Getting Started
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### 1. Requirements
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Visual Python is an extension to Jupyter Notebook, so you must have Jupyter Notebook installed already.<br>
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- Python version 3.x
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- Jupyter notebook environment
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### 2. How to Install
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**1) Install package from**
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```
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pip install visualpython
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```
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**2) Enable the package**
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```
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visualpy install
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```
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**3) Activate Visual Python on Jupyter Notebook**
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Click orange square button on the right side of the Jupyter Notebook menu bar.
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### 3. Package Control Info
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* Usage: visualpy **[option]** <br>
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* Optional arguments:
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```
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help - show help menu
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install - install packages
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uninstall - uninstall packages
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upgrade - version upgrade
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version - version check
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```
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## Contributing
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If you are interested in contributing to the Visual Python, please see [`CONTRIBUTING.md`](CONTRIBUTING.md). <br>
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All skills from programmers, non-programmers, designers are welcomed.
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* Programming Guide: [Developer Documentation](https://bird-energy-733.notion.site/visualpython-docs-85c0274ff7564747bb8e8d77909fc8b7)
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* GUI Design Guide: [Visual Python GUI Kit 1.0](https://www.figma.com/community/file/976035035360380841)
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## License
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GNU GPLv3 with Visual Python special exception (See LICENSE file).
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## Mission & Vision
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**Mission** <br>
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To support technology and education so that anyone can leverage big data analytics to create a variety of social values.
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**Vision** <br>
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To create an environment where everyone can learn and use big data analytics skills easily.
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## Support Visual Python
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Love Visual Python? <br>
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Your support will help us continue to actively develop and improve Visual Python.☕
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<a href="https://www.buymeacoffee.com/visualpython" target="_blank"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=visualpython&button_colour=ffa238&font_colour=000000&font_family=Comic&outline_colour=000000&coffee_colour=FFDD00"></a>

‎SUMMARY.md

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# Table of contents
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## GETTING STARTED
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* [Welcome to Visual Python](README.md)
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* [How to install](getting-started/how-to-install.md)
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* [Installing FAQ](getting-started/installing-faq.md)
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## TUTORIALS
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* [Data Preparation](tutorials/data-preparation.md)
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* [Data Exploration](tutorials/data-exploration.md)
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* [Data Transformation](tutorials/data-transformation/README.md)
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* [Modify DataFrames](tutorials/data-transformation/modify-dataframes.md)
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* [Create Subsets](tutorials/data-transformation/create-subsets.md)
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* [Group & Aggregate DataFrames](tutorials/data-transformation/group-and-aggregate-dataframes.md)
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* [Combine DataFrames](tutorials/data-transformation/combine-dataframes.md)
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* [Reshape DataFrames](tutorials/data-transformation/reshape-dataframes.md)
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## RESOURCES
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* [License](resources/license.md)
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* [Brand Story](resources/brand-story.md)
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* [Community](resources/community.md)

‎getting-started/how-to-install.md

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---
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description: This document will show how to install Visual Python.
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---
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# How to install
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{% hint style="info" %}
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**Visual Python** is an extension to [Jupyter Notebook](https://jupyter.org/), so you must have Jupyter Notebook installed already.&#x20;
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{% endhint %}
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{% embed url="https://www.youtube.com/watch?v=d-nR-ADpObU" %}
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### Pip Installation
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**1. Install package from**
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```
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pip install visualpython
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```
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**2. Enable the package**
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```
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visualpy install
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```
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**3. Activate Visual Python on Jupyter Notebook**
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Click orange square button on the right side of the Jupyter Notebook menu.
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**4. Package Control Info**
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Version Check
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```
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visualpy version
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```
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Version Upgrade
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```
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visualpy upgrade
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```
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&#x20;Uninstall
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```
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visualpy uninstall
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```
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Help Menu
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```
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visualpy help
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```
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‎getting-started/installing-faq.md

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# Installing FAQ
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### Which web browsers does Visual Python support?
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{% hint style="info" %}
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Visual Python may work on many up-to-date browsers but it is optimized for Chrome.
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{% endhint %}
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### I installed Visual Python, but the orange button does not appear on my Jupyter Notebook.
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This can happen if the you're using a Python version is not 3.x.&#x20;
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1. Please upgrade to Python 3.x, or
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2. If you are using multiple versions of Python, specify the pip version as 3 using the following command:
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**NOTE:** Please uninstall before reinstalling.&#x20;
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```
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pip uninstall visualpython
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```
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```
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visualpy install —pip3
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```
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### How can I install Visual Python behind a corporate firewall?
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If pip installation gives you SSLError, it can be solved using the following command:
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```
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pip install visualpython --trusted-host pypi.org --trusted-host files.pythonhosted.org
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```
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To upgrade Visual Python in the same environment, follow the steps below.
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**1) Upgrade Visual Python package.**
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pip install visualpython --upgrade --trusted-host pypi.org --trusted-host files.pythonhosted.org
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```
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**2) Enable the package.**
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```
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visualpy install
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```
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‎resources/brand-story.md

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# Brand Story
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**Visual Python** is an open source project started for students who struggle with coding during Python classes for data science.
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Just as the sun rises and the vision brighten, Visual Python is designed with the concept of giving hope and bright energy to people who are struggling with coding Python.
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Inspired by the rising sun, bright orange and yellow gradation colors are used for the logo.
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![](<../.gitbook/assets/Group 978.png>)
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****
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**Our Mission**
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To support technology and education so that anyone can leverage big data analytics to create a variety of social values.
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**Our Vision**
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To create an environment where everyone can learn and use big data analytics skills easily.
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**Our Core Values**
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Clear and Concise / Liberty and Responsibility / Knowledge share
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‎resources/community.md

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# Community
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### **GitHub**
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[github.com/visualpython/visualpython](https://github.com/visualpython/visualpython)
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Visit our GitHub repository if you are interested in contributing, or to check out the community.
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### Buy Visual Python a coffee
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[buymeacoffee.com/visualpython](https://www.buymeacoffee.com/visualpython)
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Love Visual Python?\
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Your support will help us continue to actively develop and improve Visual Python.☕
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\
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‎resources/license.md

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# License
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The Visual Python is licensed under the GNU General Public License version 3.0 with the Visual Python special exception. (See [LICENSE](https://github.com/visualpython/visualpython/blob/main/LICENSE))
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We hope to continue to develop and improve Visual Python with open source community to make better software for everyone.
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_<mark style="color:green;">hello@visualpython.ai</mark>_
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<mark style="color:orange;"></mark>
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<mark style="color:orange;"></mark>

‎tutorials/data-exploration.md

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---
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description: This document will show how to do EDA with Visual Python.
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---
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# Data Exploration
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{% embed url="https://www.youtube.com/watch?v=DMdSJ2XMHKk" %}
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### To explore the data&#x20;
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1. Click on the <mark style="color:green;">**Profiling**</mark> app.
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2. Check the library installation, and import.
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3. Select a DataFrame to explore.
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4. Click <mark style="color:green;">**Generate Report**</mark>** **<mark style="color:orange;">****</mark> button.
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[Pandas Profiling](https://github.com/ydataai/pandas-profiling) is a great library for quick EDA. This interactive report can be exported to HTML format.&#x20;
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‎tutorials/data-preparation.md

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---
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description: >-
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This document will show how to import Python libraries and read data files
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with Visual Python.
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---
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# Data Preparation
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{% embed url="https://www.youtube.com/watch?v=JrtkV_MpS0E" %}
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### To import packages/libraries
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Before starting, we need to import essential Python libraries.
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1. Click on the <mark style="color:green;">**Import**</mark> app from the menu
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2. Select libraries you need
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3. Click <mark style="color:green;">**Run**</mark> button to generate code.
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Numpy, Pandas, Matplotlib are the most primarily used libraries for data analysis. You can also add other libraries with <mark style="color:green;">**+ Module**</mark> / <mark style="color:green;">**+ Function**</mark> buttons.
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### To read data from a file
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Now, we need a dataset to analyze.
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1. Click on the <mark style="color:green;">**File**</mark> app, to read data files.&#x20;
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2. Identify the data type: CSV, Excel, JSON, Pickle are supported
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3. Click on the folder icon to open the file explorer.
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4. Use additional options if necessary.
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5. Click <mark style="color:green;">**Run**</mark> !
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‎tutorials/data-transformation/README.md

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# Data Transformation
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‎tutorials/data-transformation/combine-dataframes.md

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# Combine DataFrames
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{% embed url="https://www.youtube.com/watch?v=gbU66-NsTc4" %}
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### To combine DataFrames
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1. Click on the <mark style="color:green;">**Bind**</mark> app.
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2. Select combining method:
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{% hint style="info" %}
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* <mark style="color:green;">**Concat**</mark>: to stack up multiple DataFrames along rows or columns.
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* <mark style="color:green;">**Merge**</mark>: to combine DataFrames based on values in shared columns.
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{% endhint %}
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**Concat**
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1. Select variables to combine.
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2. Select the axis to concatenate along.
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3. and then <mark style="color:green;">**Run**</mark> !
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![](<../../.gitbook/assets/image (14).png>)
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**Merge**
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1. Select Left & Right data to merge.
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2. Select key columns to merge on.
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![](<../../.gitbook/assets/image (6).png>)
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