A choropleth map of the contiguous United States showing maternity care access by county. Counties are classified into three categories: Maternity Care Desert (deep red), Limited Access (muted tan), and Full Access (near-white). The map reveals large contiguous regions of zero maternity care — defined as no obstetric clinicians and no birthing facilities — concentrated across the Great Plains, rural South, and parts of the Mountain West. 4 in 10 U.S. counties fall into this category, forming unbroken voids spanning hundreds of miles rather than isolated gaps. Full Access counties cluster along the coasts, in the Upper Midwest, and in metropolitan areas. Data source: HRSA Area Health Resources Files (AHRF) 2022–2023; classification adapted from March of Dimes (2024).

📊 #SWDchallenge Mar 2026 | mapping with purpose
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4 in 10 U.S. counties have no obstetric clinicians and no birthing facilities. Not scattered gaps — contiguous voids across the Great Plains and rural South.
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🔗https://tinyurl.com/59c836uy
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#dataviz | #rstats | #DataStorytelling

Before-and-after comparison of the same education data. The left panel shows a grouped bar chart comparing expected vs. actual years of schooling across 15 countries — the paired bars make it hard to compare gaps. The right panel shows the same data as a dumbbell chart, where connected dots instantly reveal the education gap for each country. Australia, China, and Brazil have the largest gaps (7+ years), while USA, South Africa, and Japan have the smallest (around 2-3 years). The visualization demonstrates the SWD lesson: if a chart feels hard to read, try a different format.

📊 #SWDchallenge Feb 2026
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Grouped bars felt cluttered. Switched to dumbbells. The education gap became instantly clear.
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Lesson: If it feels hard to read, it probably is. Trust your instincts.
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🔗 stevenponce.netlify.app/data_visuali...
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#dataviz | #rstats | #ggplot2

Stacked bar chart showing Steam achievement unlock rates for The Witcher 3's eight story milestones. Each bar represents 100% of players. Purple segments show players who reached each milestone; gray segments show those who didn't. The first milestone (Tutorial Complete) shows 60.7% reached, while the final milestone (Game Complete) shows only 22.2% reached—a 38.5 percentage point drop. The purple segments visibly shrink from left to right, demonstrating that most player journeys are partial: many started but didn't finish.

📊 #SWDchallenge Jan 2026 | plot partial information
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60% started Geralt's journey. Only 22% finished it.
. 🔗stevenponce.netlify.app/data_visualizations/SWD%...
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#dataviz | #rstats | #DataStorytelling

Line chart showing the cumulative home run trajectories for all 28 members of baseball's 500 Home Run Club. Three players are highlighted: Mark McGwire in red reached 500 HR fastest at 1,688 games, but is linked to PED use; Babe Ruth in dark blue holds the fastest clean record at 1,790 games; Eddie Murray in teal took the longest at 2,971 games. The remaining 25 players appear as gray lines, illustrating a spread of roughly 1,300 games between the fastest and slowest paths to the milestone.

📊 #SWDchallenge Dec 2025 | when less is better
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The race to 500 home runs: McGwire fastest at 1,688 games (PED-linked), Ruth holds the clean record at 1,790.
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🔗 stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2 | #DataStorytelling

Dot plot showing median speed for 18 Pokémon types, ranked from fastest to slowest. Flying types are fastest with a median of 116, while Fairy types are slowest at 49. Gray bars show the full range (min-max) for each type. A dashed vertical line marks the overall median speed of 65.

📊 #SWDchallenge Nov 2025 | discover the dot plot
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Pokémon speed hierarchy: Flying dominates at 116, Fairy trails at 49.
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🔗 stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2 | #DataStorytelling

Arrow chart showing changes in non-profit funder support from 2020 to 2025. Health increased by 8% to 75%, while Arts & Culture grew by 23% to 43%. Education declined by 13% to 60%, Human Services fell by 5% to 55%, and Other dropped by 23% to 30%. A dashed vertical line marks the 2025 median at 55%.

📊 SWD Challenge - OCT 2025: Avoiding the Spaghetti Graph
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Directional arrows replace tangled lines. Health surged, Education slipped.
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🔗 stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2 | #DataStorytelling

Two-part comparison showing traffic dashboard redesign. Top image: "Before" - cluttered interface with multiple tabs (Overview, Volume, Speed, Vehicles, Data), numerous sidebar controls, and scattered KPI boxes showing 396,077 total volume, 41.7 avg speed, 3.8% large vehicles. Multiple charts compete for attention across a tabbed layout. Bottom image: "After" - clean single-page design with streamlined sidebar (3 controls only), prominent KPIs at top (28,906 avg daily volume, 44 mph median speed, 3.8% large vehicles), and two focused charts: daily traffic volume trend and weekday vs weekend hourly profile comparison.

📊 #SWDchallenge – SEP 2025 | dashboards that deliver
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Transformed a cluttered traffic dashboard from 8 controls + 5 tabs into a focused single-page solution for transport planners.
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🔗: stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #shiny | #dashboarddesign

Four-slide strategic sourcing presentation showcasing a transformation from a 17x industry benchmark overspend to $1.3M in annual savings. Slide 1 displays a bar chart comparing the current $50M spend with the industry standard of $2.8M. Slide 2 shows a quadrant analysis, identifying Supplier C as the optimal choice (green dot in the bottom-right quadrant, characterized by high performance and low cost). Slide 3 presents three forecast scenarios through 2028, with a dual supplier strategy (green line) resulting in $1.27M in savings compared to the status quo (red line). The title slide introduces the data-driven supplier strategy approach.

📊 #SWDchallenge JUN 2025 | transform a graph
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From 17x overspend to $1.3M savings 💰
🚨 $47M overspend vs industry
📈 Quadrant supplier analysis
✅ Strategic sourcing solution
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Combined chart showing client contact program results. Top panel: horizontal bar chart with Executive Services showing +20 percentage point improvement (blue), Travel & Experiences +8pp (dark gray), Elite Access +2pp (light gray), and Lifestyle Services -3pp decline (red). Bottom panel: slope chart showing performance trends from before to after the program, with Executive Services rising steeply from 69% to 89% (blue line), while Lifestyle Services declined from 75% to 72% (red line). Gray lines show Travel & Experiences and Elite Access with modest improvements. A 90% target line is marked.

📊 #SWDchallenge – MAY 2025 | which chart shows it best?
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Strategic chart combo: diverging bars + slope charts = executive-ready insights! 🎯
Result: Clear "celebrate vs intervene" decisions.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

A ridgeline plot shows how disaster death distributions changed from 1950 to 2020 across five major disaster types: Drought, Flood, Earthquake, Extreme Weather, and Extreme Temperature. The visualization uses a rainbow color gradient from blue (1950s) to red (2020s) to display density curves of death patterns for each decade. The graph reveals shifting mortality distributions over time, with apparent variations in pattern and magnitude across different disaster types. Deaths are shown on a logarithmic scale from 0.1 to 1M.

📊 #SWDchallenge – MAY 2025 | compare human and machine
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Transformed disaster death data into ridgeline plots revealing hidden patterns across seven decades.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Retail department performance visualization with two charts. Top chart shows year-over-year growth trends from Jan 2024 to Mar 2025, highlighting the three most volatile departments (Grocery, Hardware, and Toys) with Grocery showing the most dramatic fluctuations. Bottom chart plots standard deviation against mean growth rate for all departments, revealing that departments with higher volatility (like Grocery) don't necessarily have the highest average growth rates.

📊 #SWDchallenge – MAR 2025 | resist the temptation to show all the data
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Data visualization showing youth vaping rates from 2012-2023 across 37 countries. The top graph reveals rates increasing from 0.3% to 13.9% despite two policy interventions in 2016 and 2018. The bottom chart quantifies policy failure through three metrics: high annual growth rate (+38.5%), a significant gap between youth and adult usage (7.5 percentage points), and current rates far exceeding target levels (+8.9 percentage points above 5% target).

📊 #SWDchallenge Mar 2025 | present disappointing results
Visualizing policy failure: OECD data shows youth vaping rates surged 190% despite regulatory interventions.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

A dual-panel visualization titled TrueNut's Market Dominance in Powdered Nut Butter. The left panel shows a quadrant chart positioning TrueNut as a market leader with 100% category coverage and high market share, NutBrite as a specialist with high coverage but lower share, and GoldenSpread as a limited player with low coverage and share. The right panel displays a dumbbell chart showing sales by product category, with TrueNut leading in most categories, particularly in Peanut Butter ($71.9M) and Hazelnut Spread ($73.81M).

📊 #SWDchallenge – FEB 2025 | go crazy or keep it simple
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Transformed a complex Mekko chart into quadrant & dumbbell visualizations, revealing TrueNut's 70% dominance in the $386M nut butter market.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

A streamgraph visualization showing harvested acres of five major U.S. fresh vegetable crops from 2000 to 2022. The graph reveals layers of production with Sweet Corn and Tomatoes dominating at over 60K acres each by 2020. Smaller production areas are shown for Squash, Spinach, and Potatoes. The visualization uses color-coding and connecting lines with dots to identify each vegetable type. An upward trend in overall production is notable after 2010.

📊 #SWDchallenge Feb 2025 | reclaim the streamgraph
Analyzing 5 major U.S. fresh vegetable crops from @USDA data using streamgraph. Sweet corn & tomatoes lead production with 60K+ acres each by 2022.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

This connected dot plot compares consumer ratings of three energy drink brands (Lime Rush, Neon Pulse, and Storm Fuel) across 10 attributes. The visualization shows that 'Supports an active day' scored the highest (~95%) across all brands. In contrast, 'Healthy energy source' showed the largest variation between brands, with Lime Rush scoring significantly lower (4%) than its competitors.

📊 #SWDchallenge – JAN 2025 | Space & Alignment Exercise
Comparing energy drink brands through a connected dot plot.
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🔗:
stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Data visualization analyzing reviews of One Hundred Years of Solitude with four plots: (1) Distribution of emotional content by rating category, showing positive emotions dominating higher ratings; (2) Emotional flow through reviews, illustrating a mix of joy, trust, and sadness across the text; (3) Review complexity by rating, indicating longer sentences in positive reviews; (4) Common word pairs in reviews, highlighting frequent terms such as 'family', 'buendía', and 'realism'.

📊 #SWDchallenge – JAN 2025 | visualize qualitative data.
Analyzing emotions in "One Hundred Years of Solitude" reviews. Exploring how 42 readers experienced García Márquez's masterpiece.
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🔗: stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Line chart showing progress in reducing working poverty rates in Africa's lower-middle-income countries from 2000 to 2019. The chart compares trends among women and men and the overall total across three age groups: Age 15 and older, youth age 15-24, and adults age 25 and older. Poverty rates declined for both men and women, with notable differences between adults and youth.

📊 #SWDchallenge – DEC 2024 | Tell me something good!
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Data from the ILO for Africa's lower-middle-income region shows progress in reducing working poverty rates by gender and age group.
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🔗: stevenponce.netlify.app/data_visuali...

#SWDchallenge | #dataviz | #rstats | #ggplot2

Line chart showing cumulative Eurovision wins by country from 1956 to 2024. Sweden and Ireland lead with 7 wins each, with Ireland's most recent win in 1996 and Sweden's in 2023. Other countries have fewer wins, depicted in gray.

Here is my #viz for the #SWDchallenge – NOV 2024 | make a good graph.
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The data for this month's challenge comes from TidyTuesday 2022, week 20: Eurovision. 🎶✨

✏️ Makeover: stevenponce.netlify.app/data_visuali...
#SWDchallenge | #dataviz | #rstats | #ggplot2

Update (October 11, 2024): This post has been updated based on valuable feedback from the #SWDchallenge community.

WakeUp Coffee Sales Summary for the top 10 accounts by sales volume for the 4 weeks ending January 31st. Account H experienced the highest growth (+37.90%) with sales totaling $11,645. Account D had the highest sales volume at $547,265. Accounts J and E both showed significant declines, with -8.70% and -4.70%, respectively. The table includes sales volume, percentage change versus prior period, average number of UPCs, percentage of ACV selling, and price per pound.

Here is my makeover of the original #table for the #SWDchallenge | Exercise - apply emphasis to this table.
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Original table: community.storytellingwithdata.com/exercises/ap....
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✏️ Makeover: stevenponce.netlify.app/data_visuali...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

Dual visualization showing astronaut mission trends and career paths. The left panel is a line chart displaying the number of missions over time, segmented by nationality (Others, U.S.S.R./Russia, U.S.). Notable events like ‘The Apollo 11 Moon Landing’ and ‘The First Space Shuttle Launch’ are annotated. The right panel is an alluvial plot depicting the flow of astronauts from nationality to mission type, gender, and occupation, highlighting key career paths.

Here is my #viz for the #SWDchallenge – OCT 2024 | trick (or treat) your tool.
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The data for this month's challenge comes from TidyTuesday 2020 week 29 Astronaut Database.
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #SWDchallenge | #dataviz | #ggplot2

This stacked bar chart showcases the number of hydrogen projects in the top 10 countries, emphasizing operational projects. The countries included are Germany, the United States, Australia, Spain, France, the United Kingdom, the Netherlands, China, India, and Denmark. The bars are divided by project status, with operational projects highlighted in orange. The United Kingdom is also singled out with the annotation "Total H2 Projects per Country," indicating its total of 110 projects. The data is from The Hydrogen Production Projects Database, and the visualization aims to underscore the distribution and status of hydrogen projects in these leading countries.

Here is my #viz for the #SWDchallenge– SEP 2024 | stack it up!
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The data for this month's challenge comes from a worldwide database of hydrogen projects (via the International Energy Agency).
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📂: github.com/poncest/SWDc...
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#rstats | #SWDchallenge | #dataviz | #ggplot2

This is a streamgraph of Athlete Counts Over Time that shows the number of athletes in the Winter and Summer Olympic Games from 1896 to 2016. The X-axis represents the years, and the Y-axis represents the number of athletes. A colorful gradient from yellow to purple depicts variations in athlete counts. Vertical gray bands highlight World War I and World War II periods when the Olympics were not held. The graph indicates fluctuations in athlete participation, with dips during the wars and overall growth over time.

Here is my #viz for the #SWDchallenge– AUG 2024 | visualize the olympics
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The data for this month's challenge comes from rgriffin via Kaggle.
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Disclaimer: This chart is more aesthetic than informative (quantitative).
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📂: github.com/poncest/SWDc...

makeover chart

original chart

Here is my #viz for the #SWDchallenge | Exercise - make the point clear
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📂: github.com/poncest/SWDc...
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#SWDchallenge | #dataviz | #rstats | #ggplot2

The image is a funnel chart titled "Drug Development Funnel." It illustrates the stages of drug development from discovery to market, with decreasing molecules at each stage. It starts with 1,000,000 molecules at the "Target Identification & Validation" stage. It narrows down to 10,000 molecules at the "Compound Screening" stage, 250 molecules at the "Hit Validation" stage, 50 molecules at the "Lead Identification & Optimization" stage, five molecules at the "Clinical Trials & FDA Approval" stage, and finally, just one molecule reaching the "Commercialization" stage.

Here is my #viz for the #SWDchallenge– JUN 2024 | make a funnel chart
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The data presented here was synthetically generated using ChatGPT 4 for illustrative purposes only.
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📂: github.com/poncest/SWDc...
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#SWDchallange | #dataviz | #rstats | #ggplot2

The image combines two scatter plots that depict the correlation between the viewership and IMDb ratings for the TV show Family Guy during its first 21 seasons. Each plot uses the season number as the x-axis, ranging from 1 to 21, and individual episodes of the show are represented as dots. The top chart tracks viewership in the US, plotted on the y-axis from 0 to 20 million viewers. A noticeable trend is that viewership was highest during the early seasons, peaking at 22 million viewers in the first episode and gradually declining over subsequent seasons. Notable episodes are highlighted, such as the series premiere "Death Has a Shadow" and "The Manchurian Candidate" from season 21. The bottom chart displays IMDb ratings, which are plotted on the y-axis from 4 to 10. This plot shows that ratings fluctuated but generally remained stable, averaging around the 7 to 8 range. The episode "Road to the Multiverse" from season 8, which scored 9.1, is highlighted.

Here is my #viz for the #SWDchallenge– MAY 2024 | when every point matters
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The data comes from Kaggle via Sourav Banerjee. This #viz is about Family Guy, an animated sitcom, seasons 1 – 21.
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📂:github.com/poncest/SWDchallenge/tre...
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#dataviz | #rstats | #ggplot2

Bump chart of Political Rights and Civil Liberties in South America, 1995 – 2024. The data series in ‘dark blue’ corresponds to the World, in ‘red’ to Venezuela, and “gray” to the rest of South American countries.

Here is my #viz for the #SWDchallenge– MAR 2024 | design for accessibility
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The data comes from TidyTuesday 2022 wk 08 & Freedom House. This #viz is about the Political Rights and Civil Liberties in South America.
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📂: github.com/poncest/SWDc...
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#SWDchallange | #dataviz | #rstats | #ggplot2

A 3x3 grid of Merry Christmas stamps in different colors (red, yellow, blue and black) featuring Christmas Trees with lights and snow in the background

Inspired by the December #SWDChallenge prompt to visualize a holiday tradition, here's an attempt to recreate Christmas themed USPS postage stamps.

I wish everyone a Merry Christmas, happy holidays and a wonderful new year!

code: github.com/curatedmess/...

#rstats