Created project structures

.github/workflows/unittests.yml

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+name: Unit Tests
+
+on:
+ push:
+ branches:
+ - master
+ pull_request:
+ branches:
+ - master
+
+jobs:
+ build:
+ runs-on: ubuntu-latest
+
+ steps:
+ - name: Checkout code
+ uses: actions/checkout@v3
+
+ - name: Set up Python
+ uses: actions/setup-python@v4
+ with:
+ python-version: '3.x'
+
+ - name: Install dependencies
+ run: |
+ python -m venv .venv
+ source .venv/bin/activate
+ pip install --upgrade pip
+ pip install -r requirements.txt
+ pip install pytest
+
+ - name: Run tests
+ run: |
+ source .venv/bin/activate
+ pytest
+
+ - name: Upload coverage report
+ if: success()
+ uses: actions/upload-artifact@v3
+ with:
+ name: coverage-report
+ path: coverage.xml

.gitignore

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+### AL ###
+# Exclude the following files and directories from remote repo
+venv/
+.venv/
+.env
+__pycache__/
+*.pyc
+.DS_Store
+Data/
+data/
+data.zip
+MachineLearningRating_v3.txt.dvc
+README.pdf

.vscode/settings.json

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+{"python.pythonPath": "venv/bin/python3"}

README.md

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 # rossmann-pharma-sales-prediction
+
+A machine learning solution to forecast sales for Rossmann Pharmaceuticals' stores across various cities six weeks in advance. Factors like promotions, competition, holidays, seasonality, and locality are considered for accurate predictions.
+The project structure is organized to support reproducible and scalable data processing, modeling, and visualization.
+
+## Project Structure
+
+```plaintext
+├── .dvc/
+│ └── config # Configuration files for data version control
+├── .vscode/
+│ └── settings.json # Configuration for VSCode environment
+├── .github/
+│ └── workflows/
+│ ├── unittests.yml # GitHub Actions workflow for running unit tests
+├── .gitignore # Files and directories to be ignored by Git
+├── requirements.txt # List of dependencies for the project
+├── README.md # Project overview and instructions
+├── scripts/
+│ ├── __init__.py
+│ ├── data_processing.py # Script for data cleaning and processing
+│ ├── data_visualization.py # Scritpt for different plots
+│ ├── load_data.py # Scritpt extracting and loading dataset
+│ ├── hypothesis_testing.ipynb # Script for hypothesis testing analysis
+├── notebooks/
+│ ├── __init__.py
+│ ├── eda_notebook.ipynb # Jupyter notebook for eda analysis
+│ ├── hypothesis_testing.ipynb # Jupyter notebook for hypothesis testing analysis
+│ ├── data_preprocessing.ipynb # Jupyter notebook for data preprocessing
+│ ├── model_training.ipynb # Jupyter notebook for statistical model training
+│ ├── README.md # Description of notebooks
+├── tests/
+│ ├── __init__.py
+│ ├── test_data_processing.py # Unit tests for data processing module
+│ ├── test_hypothesis_testing.py # Unit tests for hypothesis testing module
+│ 
+└── src/
+ ├── __init__.py
+ └── README.md # Description of scripts
+```
+# Installation
+
+>>> git clone https://github.com/epythonlab/rossman-pharma-sales-prediction.git
+
+>> cd rossman-pharma-sales-prediction
+
+### Create virtual environment
+
+>>> python3 -m venv venv # on MacOs or Linux
+>>> source venv/bin/activate # On Windows: venv\Scripts\activate
+
+### Install Dependencies
+
+>>> pip install -r requirements.txt
+
+## To run tests
+navigate 
+>>> cd tests/
+>>pytest # all tests will be tested
+

notebooks/README.md

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+# Description of notebooks

src/README.md

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+# Description of scripts