Our group wanted to look into the topic of climate trends around the world based on regions. We wanted to see how the rise in temperature over several years affected different parts of the world and how many of these countries are using sustainable energy and if that is making a difference.
Here are the datasets we used for the base of our data exploration: https://www.kaggle.com/datasets/jawadawan/global-warming-trends-1961-2022 This dataset looks at annual surface temperatures for over 100 countries spanning from 1961-2022. https://www.kaggle.com/datasets/anshtanwar/global-data-on-sustainable-energy This dataset looks at sustainable energy factors across over 100 countries from 2000 to 2020.
We wanted to answer three main questions with our visualizations:
- What amount of CO2 emissions did each country produce over 25 years? [GeoJSON Map]
- What percentage of each country’s current energy production is sustainable? [Bar Chart]
- How did the temperature averages for each country change over 25 years? [Scatter plot]
This project contains a main HTML page (link here). You can interact with this page in two different ways: scrolling down the page to view each visualization and interacting with them individually on the main page or clicking the individual hyperlinks on the main HTML page (this will open a separate HTML page for each visualization that can be interacted with).
Emissions Cloropleth Map (The map showcases c02 emissions from different countries around the world over a 20 year period. The scrollable feature at the bottom lets you change the year. The color changes based on emissions. Light yellow for under 50k kilotons to dark red for over 350k kiltons. The United States has its own scrollable feature to show how much c02 was emitted on any given year. There is also a hover popup feature that lets you scroll over the country to highlight the name and emissions for that year.)
Sustainable Energy Bar Charts (The bar charts showcase renewable energy percentages for each region from 2000 to 2019. The scrollable feature allows you to see each individual bar chart based on region. Within each chart is a bar for each country. The color of the bar corresponds with the scale on the right hand side. You can also select the year using the drop down menu. Each bar also has a hover-over feature that lists the country name, year, and renewable energy %.)
Annual Surface Temperature Scatter Plots (User can select continent on drop down. This will show each country and the change in surface temp for each year. )
Data accuracy and representation are essential when using public datasets and transforming the data within them. We looked at the sources for each of our Kaggle datasets and noted that the global warming trends dataset did not list an exact source, it references reputable climate monitoring agencies and research institutions. We acknowledge that this does not suffice as a sufficient source for the data and can have implications on the accuracy of what is depicted in the project. On the other hand, our second source for global data on sustainable energy contains reference to the data being sources from the World Bank and International Energy Agency. The main source of the data in this kaggle set is from this website https://ourworldindata.org/sdgs/affordable-clean-energy. It is important to note that there were a numerable amount of empty cells across the first and second dataset, both of which were filled with 0's as a representation of no data present, in our clean data CSV files.
We also want to note the ethical use of our visualizations in this project. We tried to avoid misleading visualizations by distorting the scale of the data. Our bar charts have consistent axis scales and our map uses the same color scheme. We want to note that there are inherit baises in the data since different regions are going to have different socio-economic and geographical factors that affect their renewable energy sources and use. This will also have an impact on temperature changes over time.
The following Kaggle datasets were used as the base of our data exploration for this project.
- https://www.kaggle.com/datasets/jawadawan/global-warming-trends-1961-2022 This dataset looks at annual surface temperatures for over 100 countries spanning from 1961-2022.
- https://www.kaggle.com/datasets/anshtanwar/global-data-on-sustainable-energy This dataset looks at sustainable energy factors across over 100 countries from 2000 to 2020.
The basis for the Emissions Cloropleth Map code was built using the code found in this notebook (https://www.kaggle.com/code/anshtanwar/starter-notebook-global-sustainable-energy). The code was modified based on our clean CSV data. The seaborn library that was used was also based on the same notebook that utilizes Seaborn to create different visualizations. Here is an image of the seaborn visualization that was used in the notebook:
We utilized https://seaborn.pydata.org/index.html as a resource to see what different kinds of visualizations could be created with the Seaborn library in Python. Ultimately, Xpert Learning Assistant and ChatGPT were used to fully curate the Seaborn visualization (for error troubleshooting and additional suggestions on cleaning up the visual).
We also want to note that it was AI that suggested we use the write.HTML function in python to create our base HTML pages for our visualizations. This additional tool was useful in saving time. Although the base HTML pages were created using a python library, Andrew created our main HTML page that integrated the three visual HTML pages. The following resources were used to assist him in that process:
- https://stackoverflow.com/questions/12032664/load-a-html-page-within-another-html-page (Loading HTML pages within HTML)
- https://www.w3schools.com/html/html_iframe.asp (iframe tutorial).
This project would not have been made possible without the following individuals: Andrew Pohle, Lauren Graves, Jessica Maranto, and Caitlin McMahill. A huge thank you to the collaborative efforts of this individuals and to the resources used to provide the foundation for this project.