Metadata-Version: 2.1
Name: wikiframe
Version: 0.0.4
Summary: Convert all csv files in a folder to a diccionary of dataframe and more
Author: MasamioNakada
Author-email: nakada2130@gmail.com
License: UNKNOWN
Keywords: pandas,read_csv,automated,dataframe,csv,etl,extract
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
License-File: LICENCE.md

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<br />
<div align="center">
  <a href="https://github.com/MasamioNakada/wikiframe">
    <img src="https://cdn.discordapp.com/attachments/826683941053399091/928700680661782628/unknown.png" alt="Logo" width="80" height="80">
  </a>

<h3 align="center">WikiFrame</h3>

  <p align="center">
    Convert all csv files in a folder to a diccionary of dataframe and more!.
    <br />
    <a href="https://github.com/MasamioNakada/wikiframe"><strong>Explore the docs Â»</strong></a>
    <br />
    <br />
  </p>
</div>



<!-- TABLE OF CONTENTS -->
<details>
  <summary>Table of Contents</summary>
  <ol>
    <li>
      <a href="#about-the-project">About The Project</a>
    </li>
    <li>
      <a href="#installation">Installation</a>
    </li>
    <li><a href="#usage">Usage</a></li>
    <li><a href="#contributing">Contributing</a></li>
    <li><a href="#license">License</a></li>
  </ol>
</details>



<!-- ABOUT THE PROJECT -->
## About The Project

WikiFrame scan all the .csv files in a folder and convert into a diccionary of dataframe, This package accept different csv delimiter and encodings. Also if you want to add transform dataframe-functions, you can add it!.

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<!-- GETTING STARTED -->

## Installation

1. Install from [PyPI](https://pypi.org/project/wikiframe/)
    ```sh
   pip install wikiframe
   ```


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<!-- USAGE EXAMPLES -->
## Usage

### Extractor:  
This function will extract all the csv files in the folder and convert them to a dictionary of dataframe.

        Parameters:
        -----------
        func : A list of functions that will be applied to the dataframe. (e.g. [func1, func2, func3])
        verbose : If True, will print the name of the dataframe that is transformed. (default False)

        Returns:
        --------
        data_dict : A dictionary of dataframe.

        Notes:
        ------
        The order of the dataframe in the dictionary is the same as the order of the csv files in the folder.
        func could be a list of functions or a single function.

Example:

```python
from wiki_tools import Extractor # Import the Extractor function

extractor = Extractor(path='path/to/folder') # path to folder with csv files

data_dictonary = extractor.extract_from_csv() # extract all csv files on a folder and convert into a dictionary of dataframe
```

### Say:
A cow helper function to say something
    Parameters:
    -----------
    something:  A string to say in console

Example:

```python

    from wiki_tools import Say # Import the Say function    
    say = Say('Hello World') # Say something
    say.cow_says_good() # Say something in cow speak
    say.cow_says_error() # Say something in cow speak
 ```

Output:
    
```
< Hello World >
 -------------
        \   ^__^
         \  (oo)\_______
            (__)\ goodðŸ™ˆ )\/\
                ||----w |
                ||     ||
 _____________
< Hello World >
 -------------
        \   ^__^
         \  (oo)\_______
            (__)\ goodðŸ™ˆ )\/\
                ||----w |
                ||     ||

```

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<!-- CONTRIBUTING -->
## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

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<!-- LICENSE -->
## License

Distributed under the MIT License. See `LICENSE.txt` for more information.

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[contributors-shield]: https://img.shields.io/github/contributors/MasamioNakada/wikiframe.svg?style=for-the-badge
[contributors-url]: https://github.com/MasamioNakada/wikiframe/graphs/contributors
[forks-shield]: https://img.shields.io/github/forks/MasamioNakada/wikiframe.svg?style=for-the-badge
[forks-url]: https://github.com/MasamioNakada/wikiframe/network/members
[stars-shield]: https://img.shields.io/github/stars/MasamioNakada/wikiframe.svg?style=for-the-badge
[stars-url]: https://github.com/MasamioNakada/wikiframe/stargazers
[issues-shield]: https://img.shields.io/github/issues/MasamioNakada/wikiframe.svg?style=for-the-badge
[issues-url]: https://github.com/MasamioNakada/wikiframe/issues
[license-shield]: https://img.shields.io/github/license/MasamioNakada/wikiframe.svg?style=for-the-badge
[license-url]: https://github.com/MasamioNakada/wikiframe/blob/master/LICENSE.txt
[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
[linkedin-url]: https://linkedin.com/in/MasamioNakada



