Inspiration

Climate change is one of the most pressing issues of our time, and I wanted to explore how data visualization could make global CO₂ emission patterns easier to understand. By turning raw emission data into interactive visuals, I hoped to spark curiosity and awareness.

What it does

CarbonLens is an interactive Plotly app that visualizes global CO₂ emissions from 1960 to 2020. Users can:

• Compare emission trends across countries and regions.
  
• Explore historical changes decade by decade.
  
• Identify patterns that reveal which countries are leading or lagging in reducing emissions.
  

How I built it

I used the Global CO₂ Emissions dataset from Kaggle and processed it into a smaller dataset for Plotly Studio (under 75MB). With Plotly’s visualization tools, I created line charts, bar comparisons, and choropleth maps to make the data more engaging and interactive.

Challenges I ran into

• Cleaning and preparing the dataset so it worked smoothly in Plotly Studio.
  
• Deciding which visualizations best tell the story without overwhelming the user.
  
• Balancing technical detail with simple storytelling for broader audiences.
  

Accomplishments that I'm proud of

• Creating an app that makes a serious topic accessible and visually compelling.
  
• Learning how to use Plotly Studio effectively for storytelling.
  
• Designing visuals that encourage users to explore data on their own.
  

What I learned

• How to prepare datasets for use in Plotly Studio.
  
• How storytelling through data visualization can shift perspectives.
  
• The importance of interactivity when presenting complex datasets.
  

What's next for CarbonLens

• Expanding the dataset with renewable energy adoption metrics.
  
• Adding predictive models to forecast future CO₂ emissions.
  
• Improving user experience with more guided story sections.
  

Built With

• kaggle
• pandas
• plotly
• python