Climate change is one of the most pressing challenges facing humanity in the 21st century
This why I chosed ECOWEATHER API, that i converted to a DataFrame.
In this project, we delve into the realm of climate change analysis and energy demand forecasting, aiming to:\
- 🌍 Explore the relationship between weather variables and energy consumption.
- 🌍 Establish a relationship between wind energy production and rain precipitation by analyzing historical data on wind energy production and rain precipitation.
- 🌍 Analyze the impact of climate change on energy demand trends.
- 🌍 Develop predictive models to forecast energy demand under changing climatic conditions.
Temperature Analysis : Analyze temperature data to identify trends in global warming, using desroptives analysis.
Temperature Distribution Analysis: The histogram helps visualize the spread and shape of the temperature data, highlighting any central tendency and variability in temperature values.
Seasonal Decomposition of the Temperature:
Seasonal Component: Represents recurring patterns or cycles in temperature that occur over the specified period (30 days in this case).
Trend Component: Indicates the long-term direction or trend in temperature data, reflecting overall changes over time.
Residual Component: Represents the remaining variation in temperature data after accounting for the seasonal and trend components, often reflecting random fluctuations or irregularities.
Relationship between wind energy production and rain precipitation: The goal is to see how wind speed and rain precipitation can impact renewable energy planning in several ways such:
- Resource Assessment.
- Wind Energy Production.
- System Integration.
Effect of Humidity on Renewable Energy Generation: Our project seeks to investigate the hypothesis that changes in climatic variables, such as temperature, hydropower, and wind patterns, significantly impact energy demand patterns at both regional and global scales.
These libraries we have a solid foundation for performing data analysis, visualization, and exploration in the project.
| Libraries Used |
|---|
| Pandas Library 🐼 |
| Seaborn Library 📚 |
| Numpy Library 📚 |
| Matplotlib.pyplot Library 📊 |
| Requests ❓ |