# pca-pwa
`pca-pwa`, a simplified manner for insights and decision-making by visualizing complex relationships with PCA web application.
### The Purpose of the Package
- The purpose of the package is to offer a simple way of visualizing relatationships between items of any given dataset.
The user could easily obtain a pca plot without needing to configure or compile the application.
### Installation
To install `pca_pwa`, you can use pip. Open your terminal and run:
```sh
pip install pca_pwa
```
Open `IPython` or `Jupyter Notebook`
```python
>>> from pca_pwa import app
>>> app.app.run(debug=True, use_reloader=True, host='0.0.0.0', port=8082)
>>> # * Serving Flask app 'app'
>>> # * Debug mode: on
>>> # * Running on http://127.0.0.1:8082
```
Open the url: http://127.0.0.1:8082
Upload `xslx/slx` file (Excel)
- e.g.:
- Click [here](https://github.com/danymukesha/pca-pwa/raw/main/tests/samples_file.xlsx) to download the excel file
* Items/Observations should be in rows
* Variables/Features should in columns
Choose a method of imputation for missing values
Then run the pca by clicking ``Perform PCA`` button.
---------
Otherwise you can use `git clone`:
Here is the [Usage](https://github.com/danymukesha/pca-pwa/blob/main/Usage.md):
Clone the github repository
```git
git clone https://github.com/danymukesha/pca-pwa.git
```
Run the app
```sh
cd pca-pwa
python3.1 pca-pwa/app.y
# * Serving Flask app 'app'
# * Debug mode: on
# * Running on http://127.0.0.1:8082
```
Open the url: http://127.0.0.1:8082
### License
This project is licensed under the MIT License.
### Credits
Author: MIT © [Dany Mukesha](https://danymukesha.github.io/)
Email: danymukesha@gmail.com
Thank you for using `pca_pwa`!
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"description": "# pca-pwa\n`pca-pwa`, a simplified manner for insights and decision-making by visualizing complex relationships with PCA web application.\n\n### The Purpose of the Package\n- The purpose of the package is to offer a simple way of visualizing relatationships between items of any given dataset. \nThe user could easily obtain a pca plot without needing to configure or compile the application.\n\n### Installation\nTo install `pca_pwa`, you can use pip. Open your terminal and run:\n\n```sh\npip install pca_pwa\n```\nOpen `IPython` or `Jupyter Notebook`\n```python\n>>> from pca_pwa import app\n>>> app.app.run(debug=True, use_reloader=True, host='0.0.0.0', port=8082)\n>>> # * Serving Flask app 'app'\n>>> # * Debug mode: on\n>>> # * Running on http://127.0.0.1:8082\n```\n\nOpen the url: http://127.0.0.1:8082\n\n\n\nUpload `xslx/slx` file (Excel) \n\n- e.g.:\n - Click [here](https://github.com/danymukesha/pca-pwa/raw/main/tests/samples_file.xlsx) to download the excel file\n * Items/Observations should be in rows\n * Variables/Features should in columns\n\nChoose a method of imputation for missing values\n\nThen run the pca by clicking ``Perform PCA`` button.\n\n\n\n---------\n\nOtherwise you can use `git clone`:\n\nHere is the [Usage](https://github.com/danymukesha/pca-pwa/blob/main/Usage.md):\n\nClone the github repository\n\n```git\ngit clone https://github.com/danymukesha/pca-pwa.git\n```\n\nRun the app\n\n```sh\ncd pca-pwa\npython3.1 pca-pwa/app.y\n\n# * Serving Flask app 'app'\n# * Debug mode: on\n# * Running on http://127.0.0.1:8082\n```\n\nOpen the url: http://127.0.0.1:8082\n\n### License\nThis project is licensed under the MIT License.\n\n### Credits\nAuthor: MIT \u00a9 [Dany Mukesha](https://danymukesha.github.io/)\n\nEmail: danymukesha@gmail.com\n\nThank you for using `pca_pwa`!\n",
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