├── roll no 33.pdf
└── README.md


/roll no 33.pdf:
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https://raw.githubusercontent.com/Guthulasomsunil/python-project-on-data-set-prodution-of-crops-in-india/HEAD/roll no 33.pdf


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/README.md:
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 1 | # python-project-on-data-set-prodution-of-crops-in-india
 2 | Crop Analysis in India
 3 | Crop Analysis in India is a Python-based data analysis project focused on exploring agricultural patterns, crop production, and related trends across different states and regions of India.
 4 | 
 5 | The project uses powerful data science libraries like Pandas, NumPy, Seaborn, and Matplotlib to clean, analyze, visualize, and derive insights from agricultural datasets.
 6 | 
 7 | Key Objectives:
 8 | Analyze crop production data across Indian states.
 9 | 
10 | Identify major crops grown in different regions.
11 | 
12 | Visualize patterns, trends, and comparisons between crops.
13 | 
14 | Understand seasonal impacts and yield distributions.
15 | 
16 | Technologies Used:
17 | Python
18 | 
19 | Pandas (for data manipulation and analysis)
20 | 
21 | NumPy (for numerical operations)
22 | 
23 | Matplotlib (for basic plotting and visualizations)
24 | 
25 | Seaborn (for advanced, beautiful statistical graphics)
26 | 
27 | Highlights:
28 | Data cleaning and preprocessing of agricultural datasets.
29 | 
30 | Generation of multiple types of plots: bar graphs, line plots, heatmaps, scatter plots, and more.
31 | 
32 | Insightful visual storytelling about the Indian agricultural sector.
33 | 
34 | Easy-to-read code and well-structured Jupyter notebooks/scripts.
35 | 


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