This Python project analyzes financial performance data from Microsoft, Apple, and Tesla over three years (2021β2023). It includes a terminal-based chatbot that answers financial questions using clean, transformed data and year-over-year growth calculations.
- Clean and transform multi-year financial datasets
- Compute YoY growth rates for:
- Revenue
- Net Income
- Assets
- Liabilities
- Cash Flow
- Build a chatbot that answers financial queries by company and year
- Organized into modular, reusable Jupyter notebooks
- Language: Python
- Libraries: pandas, numpy, matplotlib, seaborn, plotly
- Environment: Jupyter Notebook
- Interface: Terminal chatbot using basic NLP
financial-growth-chatbot/
βββ src/
β βββ 1_data_preparation.ipynb
β βββ 2_financial_chatbot.ipynb
βββ data/
β βββ raw_data.csv
β βββ processed_data.csv
β βββ summary_metrics.csv
βββ chatbot/
β βββ chatbot_questions.txt
β βββ sample_queries.md
βββ README.md
βββ summary.txt
βββ requirements.txt
βββ LICENSE
The chatbot supports questions like:
- What is the total revenue in 2022 for Microsoft?
- What is the net income growth (%) for Tesla between 2021 and 2023?
- What is the average revenue growth rate across all years?
See chatbot/chatbot_questions.txt for a full list of supported queries.
-
Clone the repository:
git clone https://github.com/yourusername/financial-growth-chatbot.git cd financial-growth-chatbot -
Install dependencies:
pip install -r requirements.txt
-
Run the notebooks:
src/1_data_preparation.ipynbβ Prepares and processes the datasrc/2_financial_chatbot.ipynbβ Starts the chatbot
A recruiter-ready portfolio piece that blends:
- Real-world financial data
- End-to-end data pipelines
- Conversational AI using Python
Designed to showcase your skills in data science, automation, and financial analysis.
Muskan Bhatia
MCA (AI & ML) | Python Developer | AI-Powered Data Engineer
- LinkedIn: linkedin.com/in/bhmuxkan
- Hashnode: bhmuxkan.hashnode.dev
This project is licensed under the MIT License.