└── README.md


/README.md:
--------------------------------------------------------------------------------
 1 | # Data-Driven Infrastructure Analytics 🚧📊
 2 | 
 3 | A data-driven project analyzing road and bridge construction under the PMGSY (Pradhan Mantri Gram Sadak Yojana)** scheme across Indian states and UTs. This project leverages Python and data visualization tools to uncover insights, monitor progress, and support data-backed decision-making for rural infrastructure development.
 4 | 
 5 | # 📌 Objective
 6 | 
 7 | To perform exploratory data analysis (EDA) and generate meaningful visualizations that highlight the status of road and bridge works (sanctioned, completed, pending), identify regions needing attention, and understand development trends.
 8 | 
 9 | ## 🔧 Tools & Technologies
10 | 
11 | - Python
12 | - Pandas
13 | - Matplotlib
14 | - Seaborn
15 | - Jupyter Notebook
16 | 
17 | ## 📊 Key Insights
18 | 
19 | -  Comparison between sanctioned vs. completed road and bridge projects  
20 | -  Identification of top pending regions for focused infrastructure push  
21 | -  Detection of outliers and performance disparities  
22 | -  Correlation analysis to explore relationships among key metrics  
23 | -  Color-rich, clear visualizations using custom palettes and charts  
24 | -  Geo-mapping visualizations with Excel for state-wise profit analysis
25 | 
26 | 
27 | ---
28 | 
29 | ## Visualizations
30 | 
31 | - Bar Charts for sanctioned/completed projects  
32 | - Pie Charts for completed vs. pending lengths  
33 | - Correlation heatmaps  
34 | - State-wise project status  
35 | - Histogram distributions for road metrics  
36 | - India Map visualization (via Excel Maps)
37 | 
38 | 
39 | ## Key Takeaways
40 | 
41 | - Data storytelling helps transform government records into actionable insights  
42 | - EDA helps identify gaps and strengths in implementation  
43 | - Visualization is powerful for comparing regional infrastructure statuses  
44 | - Python is a flexible tool for public infrastructure analysis and reporting
45 | 
46 | 
47 | 
48 | 


--------------------------------------------------------------------------------