For the entire 30 days of April 2024, I took the #30DayChartChallenge as an opportunity to explore ASEAN and Asian datasets by creating one chart a day given a theme per day and a chart type every week. Most of the data I explored were from ASEAN and ADB with some few datasets from ILO and OECD for the theme day.
Week 1: Comparisons
Day 1: Part-to-whole - Which Industries ASEAN Mostly Work
Day 2: Neo - Impacts of 'Pre'Neocolonialism in Southeast Asia
Day 3: Makeover - Winning Without Hosting at the SEA Games
Day 4: Waffle - Agricultural Land Use in ASEAN
Day 5: Diverging - ASEAN Population by Gender and Age Group
Day 6: OECD (Data day) - International Migration Flow in OECD Countries
Day 2: Neo - Impacts of 'Pre'Neocolonialism in Southeast Asia
Day 3: Makeover - Winning Without Hosting at the SEA Games
Day 4: Waffle - Agricultural Land Use in ASEAN
Day 5: Diverging - ASEAN Population by Gender and Age Group
Day 6: OECD (Data day) - International Migration Flow in OECD Countries
Week 2: Relationships
Day 7: Hazards - Boxplots of Nitrous Oxide Emissions from World Bank
Day 8: Circular - A Chord Chart of the Import and Export Trade within ASEAN
Day 9: Major/minor - Tick / Distribution Chart of the Trades in Services in ASEAN
Day 10: Physical - Physical Paper Clip Chart of the Pupil-to-Teacher Ratio in ASEAN
Day 11: Mobile-friendly - Donut Chart on different screen sizes using the Foreign Country Visitors to ASEAN dataset
Day 9: Major/minor - Tick / Distribution Chart of the Trades in Services in ASEAN
Day 10: Physical - Physical Paper Clip Chart of the Pupil-to-Teacher Ratio in ASEAN
Day 11: Mobile-friendly - Donut Chart on different screen sizes using the Foreign Country Visitors to ASEAN dataset
Day 12: Reuters Graphics (theme day) - ASEAN International and Domestic Airport count
Week 3: Time Series
Day 19: Dinosaurs - Dinosaur Lengths Across Periods
Day 20: Correlation - Mobile phones vs Internet Access in ASEAN
Day 21: Green Energy - Green Words in the ADB Climate Change Financing 2023
Day 22: Mobility - Road Accidents in ASEAN
Day 23: Tiles - Historical Video Games Sales
Day 20: Correlation - Mobile phones vs Internet Access in ASEAN
Day 21: Green Energy - Green Words in the ADB Climate Change Financing 2023
Day 22: Mobility - Road Accidents in ASEAN
Day 23: Tiles - Historical Video Games Sales
Day 24: ILO Region for Africa (Data day) - Employment by Education Levels in Africa
Week 5: Uncertainty
Day 25: Global Change - Global Energy Consumption and Renewable Generation in 2017 Day 26: AI - AI Global Surveillance Keyword Trends
Day 27 & 28: Good/Bad & Trend - Foreign Direct Investments FDI towards ASEAN Industries
Day 29: Black’n’white - Black or White: Chess Winners by Rating
Day 30: FiveThirtyEight (theme day) - Biggest Upsets: Women's World Cup 2023
Learnings and Key Take Aways
Here are my learning and key takeaways doing this challenge:
- Focus on a few datasets (or a data portal) that has both summarized and granular datasets. Prepare and clean them up as much as possible to reduce the time working on preparing them.
- Be aware of how much time spent on exploreing, reducing and layout. I allowed myself to give 5 hours max to work on a chart, leave it for the next day or on the weekends if it takes an extra time.
- To be most accurate, reduce the amount of data restructuring or transformations as time is limited. Keep in mind that the more reshaping occurs, the more it will be vulnerable to errors. Do sample checking using manual calculations on how you arrived with the derived numbers.
- Focus on a few datasets (or a data portal) that has both summarized and granular datasets. Prepare and clean them up as much as possible to reduce the time working on preparing them.
- Be aware of how much time spent on exploreing, reducing and layout. I allowed myself to give 5 hours max to work on a chart, leave it for the next day or on the weekends if it takes an extra time.
- To be most accurate, reduce the amount of data restructuring or transformations as time is limited. Keep in mind that the more reshaping occurs, the more it will be vulnerable to errors. Do sample checking using manual calculations on how you arrived with the derived numbers.
Datasets and Illustrator Files
Observable Notebooks
Here's a link to the Observable notebooks where datasets are cleaned up and raw charts are made:
Get the access to the raw datasets and AI files where the charts are further refined and stylized:
Thank you!
Follow my Works
X (Twitter): twitter.com/josephricafort
LinkedIn: linkedin.com/in/josephricafort
Instagram: instagram.com/joricafort
Buy Visual Products
Gumroad: josephricafort.gumroad.com
Subscribe to get products updates (Soon)!
Subscribe: josephricafort.gumroad.com/subscribe
