[OC] I analyzed 6 years of Indian stock market data — Sun Pharma gave 320% returns with LOWER risk than IT and Banking sectors Statistics

What This Visualization Shows

This data visualization displays "[OC] I analyzed 6 years of Indian stock market data — Sun Pharma gave 320% returns with LOWER risk than IT and Banking sectors" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on Analyzed real NSE stock price data from January 2020

to January 2026 for 5 major Indian sectors using

Python and Yahoo Finance API.

Key findings:

1. Sun Pharma delivered 320% return — highest of all

sectors. Rs.1 lakh became Rs.4.2 lakh in 6 years.

2. Sun Pharma also had LOWER volatility (24.8%) than

IT (27.4%) and Auto (28.7%). High return with lower

risk is rare and is exactly what investors look for.

3. HUL (FMCG) has a negative Sharpe Ratio of -0.05.

This means HUL gave LESS return than a simple bank

fixed deposit while still exposing you to stock

market risk. Classic defensive stock trap.

4. HDFC Bank — India's largest private bank — returned

only 63.7% over 6 years. RBI regulatory actions and

merger uncertainty suppressed the stock.

5. All sectors have low correlation (0.23 to 0.40)

meaning holding all 5 together provides genuine

diversification benefit.

COVID crash is clearly visible in March 2020 — all

sectors dipped simultaneously then recovered at

very different speeds.

Tools: Python, Pandas, yfinance, Matplotlib, Seaborn

Data: Yahoo Finance API (real NSE data)

Full project: [github.com/surendrasinghdata/stock-sector-analysis](http://github.com/surendrasinghdata/stock-sector-analysis), which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

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Data Analysis and Insights

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Significance and Applications

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