current daily price of various commodities from different mandis 📊 Mandi Commodity Price Analysis This project analyzes the daily price variations of various commodities across different mandis (markets) in India using Python and data visualization libraries like Pandas, Seaborn, and Matplotlib.
📂 Dataset The data consists of information on:
District
Commodity
Minimum Price
Maximum Price
Modal Price
and more attributes for different commodities collected from various mandis.
📈 Features & Visualizations The project performs the following analyses:
Missing Value Analysis: Check for null/missing values in the dataset.
Correlation Heatmap: Visualize the correlation between numeric price fields using a heatmap.
Boxplot Visualization: Display the distribution of maximum prices for the top 15 districts.
Histogram with KDE: Analyze the distribution of Modal Prices with log-scaled axes.
Line Chart: Visualize Modal Prices of the first 20 entries for a quick trend view.
Pie Chart: Show the commodity proportion in the top district based on occurrences.
Barplot: Compare the average Modal Price of commodities across the top 5 districts.
Scatterplot Comparison: Compare Min, Max, and Modal prices for the top 15 commodities in a scatter plot.
🛠️ Technologies Used Python 3
Pandas
NumPy
Seaborn
Matplotlib
📌 Purpose The goal of this project is to:
Understand price distribution and variations of agricultural commodities.
Identify top-performing districts and commodities.
Visually compare different price types (Min, Max, Modal) for better decision-making and market analysis.