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https://github.com/uhstray-io/pyrizon
Data Collection, Analysis, Mapping, Pipelining & Transformation, & API using Python
https://github.com/uhstray-io/pyrizon
api data-engineering etl numpy pandas plotly python pytorch raw-data scikit-learn seaborne sql sqlite tensorflow
Last synced: 4 days ago
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Data Collection, Analysis, Mapping, Pipelining & Transformation, & API using Python
- Host: GitHub
- URL: https://github.com/uhstray-io/pyrizon
- Owner: uhstray-io
- License: mit
- Created: 2024-07-03T02:07:01.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-01-17T19:26:52.000Z (20 days ago)
- Last Synced: 2025-01-17T20:29:24.894Z (20 days ago)
- Topics: api, data-engineering, etl, numpy, pandas, plotly, python, pytorch, raw-data, scikit-learn, seaborne, sql, sqlite, tensorflow
- Language: Python
- Homepage: https://www.uhstray.io/
- Size: 9.09 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# pyrizon
Python driven data assessment using pandas and flet
## Table of Contents
- [Platform MVP Architecture](#platform-mvp-architecture)
- [File Workflow Architecture](#file-workflow-architecture)
- [Excalidraw Design](#excalidraw-design)
- [Installation](#installation)
- [Package manager](#package-manager)
- [Dependencies](#dependencies)
- [Libraries](#libraries)
- [Sample Data Sources](#sample-data-sources)
- [Solar Flares](#solar-flares)
- [Adult Census Data](#adult-census-data)
- [EUR USD 2002-2020 Forex Data](#eur-usd-2002-2020-forex-data)
- [Reference](#reference)
## Platform MVP Architecture
## Contributing Guidelines
- [Review our Code of Conduct](https://www.uhstray.io/en/code-of-conduct)
- [Check our CONTRIBUTING.MD](./CONTRIBUTING.md)
### File Workflow Architecture
### Excalidraw Design
## Installation
### Package manager
https://github.com/astral-sh/uv
### Dependencies
```bash
pip install uv
uv sync
```
#### Libraries
```python
import pandas as pd
#TFIDF Feature Extraction Scikit-learn
import sklearn.feature_extraction.text as sk_text
import mysql.connector
import dask
```
## Sample Data Sources
- [Kaggle](https://www.kaggle.com/datasets)
- [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php)
- [Google Dataset Search](https://datasetsearch.research.google.com/)
- [Data.gov](https://www.data.gov/)
### Solar Flares
Data (CSV) : https://www.kaggle.com/datasets/khsamaha/solar-flares-rhessi
License (CC0) 1.0 : https://creativecommons.org/publicdomain/zero/1.0/
### Adult Census Data
Data : Becker,Barry and Kohavi,Ronny. (1996). Adult. UCI Machine Learning Repository. https://doi.org/10.24432/C5XW20.
License (Creative Commons Attribution 4.0) : https://creativecommons.org/licenses/by/4.0/legalcode
### EUR USD 2002-2020 Forex Data
Data : https://www.kaggle.com/datasets/imetomi/eur-usd-forex-pair-historical-data-2002-2019?select=eurusd_minute.csv
License (AGPL-3.0): https://www.gnu.org/licenses/agpl-3.0.html
### Reference
- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
- https://scikit-learn.org/stable/modules/compose.html
- https://scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html
- https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html
- https://scikit-learn.org/stable/modules/metrics.html
- https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html
- https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html
- https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfTransformer.html#sklearn.feature_extraction.text.TfidfTransformer
- https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html