What about it?
About the 30 Day Chart Challenge
The #30DayChartChallenge is a community-driven data visualization challenge that runs every April. Participants create one chart per day based on a set of prompts organized into different categories.
The Challenge
Each day has a specific prompt that guides the creation of a visualization. The prompts are organized into categories such as “comparisons,” “distributions,” “relationships,” and more. This structure encourages participants to explore different types of data visualization and improve their skills across various domains.
My Approach
For this challenge, I primarily used:
- R with packages like ggplot2, patchwork, and sf for most visualizations
- Python with libraries like matplotlib, seaborn, and plotly for specific days
- Various data sources including open data repositories, APIs, and self-collected data
Tools Used
R Packages
- ggplot2
- data.table
- sf
- patchwork
- ggtext
- waffle
- forcats
- and more!
Python Libraries
- matplotlib
- seaborn
- pandas
- numpy
- plotly
- hdx (Humanitarian Data Exchange)
Acknowledgements
- The #30DayChartChallenge community for inspiration and feedback
- Various data providers and sources used throughout the challenge
- Open source maintainers of the visualization libraries and tools