This repository contains Python code for analyzing the cumulative renewable energy capacity across various sectors in India from 2014 to 2023. The code includes:
- Importing and processing the data.
- Performing an Analysis of Variance (ANOVA) to compare the mean renewable energy capacity across different sectors.
- Interpreting the results of the ANOVA test.
- Clone this repository to your local machine.
- Open a terminal and navigate to the repository directory.
- Install the required libraries:
pip install pandas scipy
The data for this analysis contains the following columns:
| Column | Description |
|---|---|
| Sector | Name of the renewable energy sector. |
| Year | Year (format: YYYY-YY). |
| Cumulative Achievements | Cumulative renewable energy capacity (MW) for each sector and year. |
- Open a terminal in the repository directory.
- Run the following command:
python ANOVA.py
The F-statistic and p-value from the ANOVA test will be printed to the console. Interpret the results based on:
- Significant difference: P-value < 0.05 indicates a statistically significant difference in mean renewable energy capacity across sectors.
- No significant difference: P-value > 0.05 suggests no statistically significant difference in mean renewable energy capacity across sectors.
This code provides a foundation for exploring the data further:
- Visualizations: Create charts and graphs to visualize trends.
- Post-hoc tests: Identify specific sectors with significant differences.
- Growth trends: Analyze the growth of individual sectors.
- Influencing factors: Investigate factors affecting sector growth.
This repository is open-source and welcomes contributions. Please fork the repository, make enhancements, and submit pull requests.
This project is licensed under the MIT License.