Power BI Amplified with Python

This repository contains a collection of Python scripts designed to complement and enhance data analysis capabilities, combining financial analysis, text processing, and data visualization.

Overview

The project is organized into three main components:

• Financial data acquisition
• Data processing and analysis
• Results visualization

Project Structure

1. Data Acquisition

• 001_obtaining_data.py: Downloads historical stock data using yfinance
  • Retrieves NVIDIA (NVDA) data
  • Period: last 5 years
  • Includes historical prices and volume

2. Data Processing

• 002_munging_data_1.py: Text Analysis

  • Calculates comment length
  • Text data preprocessing

• 003_munging_data_2.py: Sentiment Analysis

  • Implements sentiment analysis using TextBlob
  • Generates polarity scores for comments

3. Data Visualization

• 004_render_data_0.py: Sample Demographic Data

  • DataFrame with personal information
  • Variables: name, age, weight, gender, state, children, pets

• 005_render_data_1.py: Scatter Plots

  • Age vs Weight relationship visualization
  • Implemented with matplotlib

• 006_render_data_2.py: Bar Charts

  • Age by name visualization
  • Demographic comparisons

• 007_render_data_3.py: Line Charts

  • Comparison of number of pets and children
  • Multiple visualization in a single plot

Requirements

pandas
matplotlib
pandas_datareader
yfinance
textblob

Main Features

• Automatic financial data download
• Text sentiment analysis
• Multiple customizable visualizations
• Demographic data processing
• Comparative variable analysis

Usage

The scripts are numbered sequentially to follow a logical workflow:

1. First, obtain financial data
2. Then, process and analyze the data
3. Finally, create visualizations

Notes

• Ensure you have an internet connection for financial data download
• Visualization scripts can be modified to adapt to different datasets
• Sentiment analysis works best with English text

Contributions

Contributions are welcome. Please feel free to:

• Report issues
• Suggest improvements
• Submit pull requests