DataFun-03-Analytic

(Finalize DataFun-03 project: fetch, process, and log all data types)

A Python project to fetch, analyze, and log data from multiple formats:

• CSV
• Excel
• JSON
• Plain Text (TXT)

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Project Goals

This project demonstrates how to:

• Fetch web data using requests
• Save data in multiple formats (CSV, Excel, JSON, TXT)
• Analyze the data using pandas and standard Python libraries
• Log operations using a reusable logger (utils_logger.py)

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How to Run Each Script

1. Activate the virtual environment:

.venv\Scripts\activate

2. Run each script:

python example_get_csv.py
python example_get_excel.py
python example_get_json.py
python example_get_text.py

3. View logs:

logs/project_log.log

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Python Files Overview

File	Description
example_get_csv.py	Fetches a CSV file from the web and analyzes it
example_get_excel.py	Downloads and analyzes an Excel file
example_get_json.py	Fetches JSON data about astronauts and analyzes it
example_get_text.py	Downloads a Shakespeare text and performs basic text analysis
utils_logger.py	Logger utility used by all scripts

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Project Structure

├── example_data/ │ ├── 2020_happiness.csv │ ├── astros.json │ ├── Feedback.xlsx │ └── romeo.txt │ ├── logs/ │ └── project_log.log │ ├── example_get_csv.py ├── example_get_excel.py ├── example_get_json.py ├── example_get_text.py │ ├── example_process_csv.py ├── example_process_excel.py ├── example_process_json.py ├── example_process_text.py │ ├── happiness_ladder_score_stats.txt ├── json_astronauts_by_craft.txt ├── text_romeo_word_count.txt │ ├── main.py ├── requirements.txt ├── README.md └── utils_logger.py

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Technologies Used

• Python 3.11+
• requests
• pandas
• logging
• pathlib
• json

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What I Learned

• How to work with different file formats
• How to use Python to automate data fetching and analysis
• How to use logging for debugging and auditability
• How to follow a professional Git + VS Code workflow

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Project Purpose (Course Context)

This project is part of the Data Fundamentals course
at Northwest Missouri State University.

It helps students:

• Practice using Python modules and functions
• Learn data processing and file handling
• Document and manage projects in a clean structure

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Author

Sabri Hamdaoui
Master’s Student in Data Analytics
Northwest Missouri State University
GitHub: github.com/sabrouch36

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Project Setup Process

1. Cloned the Repository

git clone https://github.com/YOUR_USERNAME/datafun-03-analytics.git
cd datafun-03-analytics
code .

2. Created and Activated a Virtual Environment

python -m venv .venv
.venv\Scripts\activate

3. Installed Project Dependencies

pip install -r requirements.txt

4. Ran the Project

python main.py