Creating Multiple Visualizations From One Data Set

Data visualization is more than simply a tool for displaying information; it's also an effective technique to convey stories. The way you present facts can significantly impact the narrative it communicates. Whether you're showing trends across time, comparing different categories, or highlighting geographical distribution, the visualization you choose influences the insights that appear.

The beauty of data is its flexibility. The same dataset can be displayed in a variety of ways, each providing a unique perspective and highlighting different features of the data. This adaptability allows for a deeper understanding of the subject at hand, as different visualizations can show patterns, trends, and relationships that might not be immediately obvious.

To better understand this idea, we took on the task of producing various visualizations from a single dataset: Global Renewable Energy Consumption from 1990 to 2020. The aim is to create as many smart visualizations as possible, each with a unique perspective on the data and highlighting the value of great data storytelling.

https://www.kaggle.com/datasets/jamesvandenberg/renewable-power-generation?

Visualizations

1. Line Chart: Tracking Progress Over Time

A line chart is a classic approach for displaying trends. Plotting renewable energy production over three decades shows how global efforts have increased, reflecting improvements in policy, technology, and cultural awareness.

Data:? Global Consumption from 1990 (102K TWh) to 2020 (168K TWh).

https://www.kaggle.com/datasets/jamesvandenberg/renewable-power-generation?select=Continent_Consumption_TWH.csv?

2. Column Chart: Understanding the Energy Mix

A column chart can effectively break down the global energy mix—fossil fuels, nuclear, and renewables—for a specific year. By comparing the height of each column, this chart shows a clear visual representation of how much each energy source contributes to the overall energy consumption.

Data: Top 10 countries generating the most power with renewables (2017)

3. Heat Map: Visualizing Regional Variations

A heat map can efficiently illustrate regional changes by using color intensity to reflect energy consumption volume. This gives a fast summary of where renewable energy is flourishing and where it is still developing.

Data: National Power Consumption 1990 -2020

https://www.kaggle.com/datasets/jamesvandenberg/renewable-power-generation?select=Country_Consumption_TWH.csv?

4. Pie Chart: Comparing Contributions by Region

A pie chart is ideal for comparing the contributions of different areas to global energy consumption. Each slice of the pie reflects a region's part of total global energy consumption, allowing for a fast comparison of their relative contributions and highlighting the regions with the highest consumption.

Data: Continental and Group Power Consumption (TWh) in 2020

5. Map: Geographical Distribution

A map visualization can indicate trends in global energy use. This can emphasize places with high energy consumption, which may be associated with more industrial activity or living standards, as well as regions with lower consumption, indicating either greater energy efficiency or less access to energy supplies.

Data: https://www.kaggle.com/datasets/anshtanwar/global-data-on-sustainable-energy?

6. Stacked Area Chart: Consumption Profiles of Top Emitters

A stacked area chart can effectively represent the energy consumption profiles of the highest emitting regions over time. This visualization helps to understand the cumulative growth in energy consumption per capita by demonstrating how different regions have contributed to global energy use and highlighting the difference between high and low emitters.?

By focusing on per capita consumption, this chart can reveal trends in energy use efficiency and the influence of population growth on energy demand.

Data: https://www.kaggle.com/code/olgashevtsova/3-energy-the-world-and-the-city?

7. Bubble Chart: Consumption vs. Population

A bubble chart provides a comparative view at energy consumption relative to population size. Larger bubbles can represent higher consumption, while the axes represent population, providing insights into energy use efficiency and regional demands.

Data:? https://www.kaggle.com/code/olgashevtsova/3-energy-the-world-and-the-city/notebook?

8. Treemap Heading: Visualizing Energy Source Contributions

The treemap illustrates the relative contributions of different energy sources to the global energy mix. This visualization enables quick recognition of the leading energy sources and their respective roles in the global energy landscape.?

Data: Global TWh power generation of from non-renewable sources (2017)

The Takeaway

Each of these visualizations provides a unique take on the same dataset. Some will be more meaningful than others, depending on the story you want to convey. However, the essential takeaway is the significance of selecting the appropriate representation to express the information you want to highlight.

When it comes to using data for creating narratives, there are limitless possibilities. Whether you're looking for trends, comparisons, or geographic distribution, the appropriate visualization may reveal new insights and make difficult data more accessible and interesting.

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