https://github.com/danymukesha/pca-pwa
simplified manner for insights and decision-making by visualizing complex relationships with PCA web application
https://github.com/danymukesha/pca-pwa
pca statistics unsupervised-learning
Last synced: 8 months ago
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simplified manner for insights and decision-making by visualizing complex relationships with PCA web application
- Host: GitHub
- URL: https://github.com/danymukesha/pca-pwa
- Owner: danymukesha
- License: mit
- Created: 2024-01-07T09:47:06.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-21T08:48:48.000Z (over 2 years ago)
- Last Synced: 2025-02-05T04:06:06.134Z (over 1 year ago)
- Topics: pca, statistics, unsupervised-learning
- Language: Python
- Homepage: https://pypi.org/project/pca-pwa/
- Size: 201 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# pca-pwa
[](https://github.com/danymukesha/pca-pwa/actions/workflows/main.yml)
`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
- **Standard Data (table) Format**
The example of standard data format to be used while uploading to pca-pwa web app is a dataframe from sample names
in the first column, and the rest (e.g.: metabolites, genes, RNA, etc.) for each sample in the following columns (see Table 1).
**Table 1:** ***Standard data table format.***
| Sample | Met 1 | Met 2 | Met 3 | ... | Met N |
|--------|---------|---------|---------|---------|---------|
| S1 | 99,380 | 10.177 | 51.484 | ... | 71.882 |
| S2 | 101.195 | 10.786 | 50.446 | ... | 73.318 |
| S3 | 102.165 | 9,375 | 49.668 | ... | 72,056 |
| S4 | 99.481 | 8.291 | 48.111 | ... | 73.282 |
| S5 | 101.282 | 10.867 | 50.209 | ... | 73,572 |
| S6 | 99.43 | 9.95 | 47.602 | ... | 71,983 |
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`!