Renewable Energy Production Visualization in R

Due to climate change and decreasing fossil fuels, it is important to focus on renewable energy production to maintain the balance. R is a statistical programming language that provides multiple such libraries, making data analysis and visualization easier. Visualizing renewable energy production trends becomes crucial with the increasing urgency to transition to cleaner energy sources. This article explores renewable energy production using a comprehensive dataset and demonstrates how R Programming Language can be employed for insightful visualizations and analysis.

Global Renewable Energy Production Visualization

Renewable energy production is a critical aspect of the global energy landscape. As countries strive to reduce their carbon footprint and transition to cleaner energy sources, visualizing renewable energy production data becomes essential for understanding trends, making informed decisions, and tracking progress.

Dataset Link:Global Renewable Energy Production

1: Install and Load Required Libraries

Firstly we will install the libraries and packages in R that help in data manipulation and visualization. In this article, ggplot2 will play the most important role as it is a powerful library used for graphs and plots.

2: Prepare the Data

Ensure your data is in the correct format and aggregate the energy data by country.

Output:

 Year Country SolarEnergy WindEnergy HydroEnergy OtherRenewableEnergy TotalRenewableEnergy
1 2000 USA 437.0861 1435.9286 1544.3897 319.3963 3736.801
2 2001 USA 240.4168 402.7929 398.7421 439.7793 1481.731
3 2002 USA 641.0035 1120.4944 334.9936 486.4594 2582.951
4 2003 USA 849.1984 476.0408 609.1024 132.5320 2066.874
5 2004 USA 373.8180 882.1834 1034.3065 181.0531 2471.361
6 2005 USA 650.6676 381.3420 796.6459 214.8628 2043.518

3. Visualization and Analysis

Now we will visualize the Renewable Energy Production Analysis.

Country-wise Comparison

We can compare the country-wise production of energy to see the highest producer of renewable energy.

Output:

We can see that France is the highest producer of total renewable energy.

Distribution of Solar Energy Production

Histograms and scatter plots help in understanding the distribution and relationships between different types of renewable energy.

Output:

Proportion of Energy country wise

We can create pie charts to show the proportion of each type of renewable energy within a country.

Output:

This code will produce a pie chart that visualizes the proportion of different types of renewable energy production in the USA for the year 2000.

Contribution of Energy country-wise

Visualize the contribution of each type of renewable energy in total production for each country.

Output:

Contribution of different types of energy

Now we will visualize the Contribution of different types of energy.

Output:

Visualize Data on the World Map

Based on the dataset we have we can visualize all kind of energy based on the world map and identify the patterns on global level. First we will analyze the merged data of world.

Output:

Conclusion

This article explored different kinds of visualization related to renewable energy production in R programming language. We observed and got various meaningful insights through different graphs which was based on global energy production.