Global CO2 Emissions - Dataset for top 25 countries
Description
The CO2-wide dataset provides carbon dioxide emissions data for the top 25 emitting countries from 1975 to 2021, measured in thousand metric tons. The dataset, sourced from UN Data, captures long-term trends in global emissions, helping researchers and policymakers analyze the impact of industrialization, economic growth, and environmental policies. Using this data, we created interactive bar charts and treemaps with D3.js, enabling dynamic visualizations that highlight emission patterns over time. These visual tools offer a clear, engaging way to explore how emissions have evolved across countries, supporting climate research, awareness, and data-driven decision-making. The dataset is available for further analysis and can be embedded into other platforms for broader accessibility.
Files
Steps to reproduce
Here are the key steps we followed in extracting, cleaning, processing, and visualizing the CO2 emissions dataset for I Hug Trees – Data Analytics: 1. Data Extraction Downloaded the CO2 emissions dataset from UN Data, which contained emission values for multiple countries over several decades. Imported the dataset into Google Sheets for an initial overview and structure assessment. 2. Data Cleaning & Preprocessing (Python & Pandas) Loaded the dataset into Pandas (Python) for cleaning and structuring. Removed irrelevant columns and filtered the data to include only the top 25 CO2-emitting countries from 1975 to 2021. Handled missing values by using interpolation or dropping incomplete rows where necessary. Converted data types to ensure consistency (e.g., numerical values for emissions). 3. Data Structuring & Formatting Rearranged the data in Google Sheets to match the structure required for visualization. Exported the cleaned dataset as a CSV file for further processing and visualization. 4. Data Visualization with D3.js (JavaScript-based Visualizations) Developed interactive visualizations using D3.js: Treemap: Showcased CO2 emissions distribution among the top 25 countries. Bar Chart: Illustrated trends over time for selected countries. Used CSV parsing functions in D3.js to load the dataset into JavaScript. Applied scaling, tooltips, transitions, and animations to enhance interactivity. 5. Embedding & Publishing Hosted the D3.js charts on I Hug Trees – Data Analytics (ihugtrees.org). Provided iframe embed codes for seamless integration into other websites. Published the cleaned dataset for open-access research and analysis. This workflow ensured high-quality, structured data and engaging interactive visualizations for better understanding global CO2 emissions trends.