This project analyzes market volatility in India using financial and economic data. The goal is to explore how market fluctuations vary across sectors, regions, and over time. The analysis includes data cleaning, feature extraction, and visualization techniques such as histograms, line plots, scatter plots, and correlation analysis. Insights are drawn for sector-wise and regional differences. And this is what I did: cleaned the data, created new features for sector, region, and time periods, transformed numeric indicators, explored the data through summary statistics and visualizations, and calculated correlations to understand the relationship between volatility and market indicators across different regions and sectors.
Import libraries
import pandas as pd
import matplotlib.pyplot as plt
import plotly.express as pxThe analysis shows that market volatility in India is influenced by both sector performance and regional factors. High volatility sectors tend to show stronger fluctuations in market value, while regional differences play a significant role in shaping risk patterns. Through data cleaning, visualization, and correlation analysis, clear trends emerged, highlighting how market indicators vary across regions and sectors. Overall, the project demonstrates how data analysis can provide actionable insights into market volatility and support informed investment strategies.