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Steven Ponce

@sponce1.bsky.social

Website: https://stevenponce.netlify.app/ GitHub: http://github.com/poncest/ LinkedIn: http://linkedin.com/in/stevenponce/

599 Followers  |  883 Following  |  257 Posts  |  Joined: 04.02.2024  |  2.0137

Latest posts by sponce1.bsky.social on Bluesky

Four-panel dashboard showing US domestic terrorism trends from 1994-2024. Panel A shows total annual attacks increased 53% from early period to recent years. Panel B displays per capita rates (attacks per million people) increased 26%, demonstrating that population growth explains half the raw increase. Panel C presents smoothed trend lines by ideology, with right-wing attacks (orange line) rising from ~8 attacks in mid-2000s to ~25 in recent years, while jihadist (teal) and left-wing (light blue) attacks remain lower. Panel D shows right-wing share of total attacks, typically 60-90%, with a notable dip to ~50% in the late 2000s. Key finding: while raw attack counts rose substantially, population-adjusted rates show a more modest increase, and right-wing attacks consistently dominate throughout the entire period.

Four-panel dashboard showing US domestic terrorism trends from 1994-2024. Panel A shows total annual attacks increased 53% from early period to recent years. Panel B displays per capita rates (attacks per million people) increased 26%, demonstrating that population growth explains half the raw increase. Panel C presents smoothed trend lines by ideology, with right-wing attacks (orange line) rising from ~8 attacks in mid-2000s to ~25 in recent years, while jihadist (teal) and left-wing (light blue) attacks remain lower. Panel D shows right-wing share of total attacks, typically 60-90%, with a notable dip to ~50% in the late 2000s. Key finding: while raw attack counts rose substantially, population-adjusted rates show a more modest increase, and right-wing attacks consistently dominate throughout the entire period.

📊 #MakeoverMonday – 2025 W45 | Terrorism and Political Violence in the United States: What the Data Tells Us
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#rstats | #DataFam | #dataviz | #ggplot2

20.11.2025 01:53 — 👍 5    🔁 0    💬 0    📌 0
Network graph showing 15 Sherlock Holmes stories (teal nodes) connected to their five most distinctive dialogue words (small grey nodes). The Sign of the Four stands out with a large purple cluster of connected words, indicating it has the most unique vocabulary among the stories. Other stories like Hound of the Baskervilles, Study in Scarlet, and Valley of Fear show smaller, more dispersed word clusters.

Network graph showing 15 Sherlock Holmes stories (teal nodes) connected to their five most distinctive dialogue words (small grey nodes). The Sign of the Four stands out with a large purple cluster of connected words, indicating it has the most unique vocabulary among the stories. Other stories like Hound of the Baskervilles, Study in Scarlet, and Valley of Fear show smaller, more dispersed word clusters.

📊 #TidyTuesday – 2025 W46 | The Complete Sherlock Holmes
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#rstats | #r4ds | #dataviz | #ggplot2

16.11.2025 12:04 — 👍 14    🔁 2    💬 0    📌 0
Four-panel dashboard showing the number of living WWII veterans by state in 2025. Panel A: diverging bar chart of veterans per 100k vs US mean, with New Hampshire highest at +29.1. Panel B: lollipop chart of the top 20 states, all above the national average of 13.7 per 100k. Panel C: histogram showing right-skewed distribution, with most states under 1,000 veterans and the top 5 states holding 37% of the total. Panel D: box plots by region showing that the Northeast has the highest concentration per capita, while the South has the most states but lower median rates.

Four-panel dashboard showing the number of living WWII veterans by state in 2025. Panel A: diverging bar chart of veterans per 100k vs US mean, with New Hampshire highest at +29.1. Panel B: lollipop chart of the top 20 states, all above the national average of 13.7 per 100k. Panel C: histogram showing right-skewed distribution, with most states under 1,000 veterans and the top 5 states holding 37% of the total. Panel D: box plots by region showing that the Northeast has the highest concentration per capita, while the South has the most states but lower median rates.

📊 #MakeoverMonday – 2025 W44 | WWII Veteran Statistics
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#rstats | #DataFam | #dataviz | #ggplot2

11.11.2025 23:12 — 👍 3    🔁 0    💬 0    📌 0
Line chart showing HIV-associated TB deaths as percentage of total TB mortality by WHO region from 2000-2024. Africa's bold blue line dominates, declining from 60% to 28% (31.9 percentage point decrease). Five other WHO regions shown in gray remain below 35% throughout, with most under 15%. All regions labeled at right endpoint. Chart demonstrates Africa's significant progress yet persistent disproportionate burden of HIV/TB co-infection.

Line chart showing HIV-associated TB deaths as percentage of total TB mortality by WHO region from 2000-2024. Africa's bold blue line dominates, declining from 60% to 28% (31.9 percentage point decrease). Five other WHO regions shown in gray remain below 35% throughout, with most under 15%. All regions labeled at right endpoint. Chart demonstrates Africa's significant progress yet persistent disproportionate burden of HIV/TB co-infection.

📊 #TidyTuesday – 2025 W45 | WHO Tuberculosis Global Burden Estimates
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#rstats | #r4ds | #dataviz | #ggplot2

09.11.2025 19:07 — 👍 8    🔁 0    💬 1    📌 0
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.

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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#SWDchallenge | #dataviz | #rstats | #ggplot2 | #DataStorytelling

01.11.2025 22:16 — 👍 4    🔁 0    💬 0    📌 0
A two-panel visualization comparing lead contamination in Flint, Michigan water samples (2015). The top panel shows a stacked bar chart with five risk categories from zero detection to above the EPA action level; Virginia Tech citizen science found 16.6% of 271 samples above the 15 ppb action level, versus the MDEQ government's 11.3% of 71 samples. The bottom panel displays cumulative distribution curves showing the percentage of samples below each lead concentration; at the 90th percentile, MDEQ measured 18 ppb, while Virginia Tech measured 26.6 ppb. The brown color palette progresses from light tan (safe) to dark brown (dangerous). Both charts emphasize EPA's health goal of 0 ppb.

A two-panel visualization comparing lead contamination in Flint, Michigan water samples (2015). The top panel shows a stacked bar chart with five risk categories from zero detection to above the EPA action level; Virginia Tech citizen science found 16.6% of 271 samples above the 15 ppb action level, versus the MDEQ government's 11.3% of 71 samples. The bottom panel displays cumulative distribution curves showing the percentage of samples below each lead concentration; at the 90th percentile, MDEQ measured 18 ppb, while Virginia Tech measured 26.6 ppb. The brown color palette progresses from light tan (safe) to dark brown (dangerous). Both charts emphasize EPA's health goal of 0 ppb.

📊 #TidyTuesday – 2025 W44 | Lead concentration in Flint water samples in 2015
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#rstats | #r4ds | #dataviz | #ggplot2

01.11.2025 18:59 — 👍 7    🔁 0    💬 0    📌 0
Bar chart showing percentage-point differences between Biden and Trump supporters on cultural issues. Blue bars extend to the right for Biden's advantages (legacy of slavery +52pp, openness +51pp, gender identity +50pp). Red bars extend left for Trump advantages (gun ownership -63pp, criminal justice -41pp, marriage priority -40pp).

Bar chart showing percentage-point differences between Biden and Trump supporters on cultural issues. Blue bars extend to the right for Biden's advantages (legacy of slavery +52pp, openness +51pp, gender identity +50pp). Red bars extend left for Trump advantages (gun ownership -63pp, criminal justice -41pp, marriage priority -40pp).

📊 #MakeoverMonday – 2025 W42 | Cultural Issues and the 2024 Election
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#rstats | #DataFam | #dataviz | #ggplot2

29.10.2025 21:51 — 👍 1    🔁 0    💬 0    📌 0
A two-panel visualization analyzing gender equity in British literary prizes from 1990 to 2022. The top panel shows a line chart of women's share of winners, which increased from 35% to 50% and showed significant year-to-year variation. The bottom panel displays a horizontal pyramid chart comparing 13 major prizes, revealing that only four achieved gender balance (40-60% women). Seven prizes remain male-dominant, and two are female-dominant, showing persistent disparities despite overall progress.

A two-panel visualization analyzing gender equity in British literary prizes from 1990 to 2022. The top panel shows a line chart of women's share of winners, which increased from 35% to 50% and showed significant year-to-year variation. The bottom panel displays a horizontal pyramid chart comparing 13 major prizes, revealing that only four achieved gender balance (40-60% women). Seven prizes remain male-dominant, and two are female-dominant, showing persistent disparities despite overall progress.

📊 #TidyTuesday – 2025 W43 | Selected British Literary Prizes (1990-2022)
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#rstats | #r4ds | #dataviz | #ggplot2

26.10.2025 11:21 — 👍 15    🔁 1    💬 0    📌 0
Data visualization with three panels analyzing the UCI Drug Consumption dataset (N=1,884). Panel 1: Line chart showing cannabis usage peaks at 80% for ages 18-24, declining with age. Panel 2: Stacked bar charts revealing polydrug patterns, with 18-24 males showing the highest 4+ drug use. Panel 3: Bar chart demonstrating conscientiousness as a protective factor, with a 10.4 percentage point reduction in heavy use between very low and very high conscientiousness groups among high-risk individuals.

Data visualization with three panels analyzing the UCI Drug Consumption dataset (N=1,884). Panel 1: Line chart showing cannabis usage peaks at 80% for ages 18-24, declining with age. Panel 2: Stacked bar charts revealing polydrug patterns, with 18-24 males showing the highest 4+ drug use. Panel 3: Bar chart demonstrating conscientiousness as a protective factor, with a 10.4 percentage point reduction in heavy use between very low and very high conscientiousness groups among high-risk individuals.

📊 #MakeoverMonday – 2025 W41 | Drug Consumptions (UCI)
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#rstats | #DataFam | #dataviz | #ggplot2

21.10.2025 22:12 — 👍 3    🔁 0    💬 0    📌 0
Combined visualization showing UK climate change from 1900-present. The top panel displays four trend charts: maximum temperature rising from ~12.5°C to 14°C, monthly rainfall increasing from 70mm to 80mm, monthly sunshine relatively stable around 115-120 hours, and air frost days declining from ~4 to 2 days. Bottom panel shows a timeline of extreme weather events with dots representing years in the top panel/bottom 5% for each metric. Extreme heat events (orange dots) cluster heavily after 1990, with 6 of 7 occurring after 2000, while extreme cold events (navy dots) become increasingly rare in recent decades. Extreme rainfall events (blue dots) are scattered throughout the period. Annotations highlight post-1990 clustering and the notable 2003 heatwave.

Combined visualization showing UK climate change from 1900-present. The top panel displays four trend charts: maximum temperature rising from ~12.5°C to 14°C, monthly rainfall increasing from 70mm to 80mm, monthly sunshine relatively stable around 115-120 hours, and air frost days declining from ~4 to 2 days. Bottom panel shows a timeline of extreme weather events with dots representing years in the top panel/bottom 5% for each metric. Extreme heat events (orange dots) cluster heavily after 1990, with 6 of 7 occurring after 2000, while extreme cold events (navy dots) become increasingly rare in recent decades. Extreme rainfall events (blue dots) are scattered throughout the period. Annotations highlight post-1990 clustering and the notable 2003 heatwave.

📊 #TidyTuesday – 2025 W42 | Historic UK Meteorological & Climate Data
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#rstats | #r4ds | #dataviz | #ggplot2

19.10.2025 22:11 — 👍 15    🔁 1    💬 0    📌 0
Two-panel chart comparing recession impacts on prime-age labor force participation (ages 25-54). The left panel shows that the 2020 recession had the steepest drop at -3.3 percentage points, compared to -1.7pp in 2001 and -1.6pp in 2008. The right panel displays recovery trajectories over 60 months: 2020 recovered fastest, exceeding pre-recession levels by +0.6pp; 2008 never recovered, remaining -1.7pp below; 2001 shows a gradual decline to -1.1pp below baseline.

Two-panel chart comparing recession impacts on prime-age labor force participation (ages 25-54). The left panel shows that the 2020 recession had the steepest drop at -3.3 percentage points, compared to -1.7pp in 2001 and -1.6pp in 2008. The right panel displays recovery trajectories over 60 months: 2020 recovered fastest, exceeding pre-recession levels by +0.6pp; 2008 never recovered, remaining -1.7pp below; 2001 shows a gradual decline to -1.1pp below baseline.

📊 #MakeoverMonday – 2025 W40 | Better things come to those who wait
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#rstats | #DataFam | #dataviz | #ggplot2

14.10.2025 22:21 — 👍 3    🔁 1    💬 0    📌 0
Line chart showing five food security indicators tracked by countries from 2005 to 2025. Four gray lines (Child Overweight, Low Birthweight, Child Stunting, Undernourishment) remain steady at 50-120 countries. One purple line (Severe Food Insecurity) dramatically rises from 35 countries in 2016 to 60 in 2022, with a gray shaded box highlighting the post-2016 period.

Line chart showing five food security indicators tracked by countries from 2005 to 2025. Four gray lines (Child Overweight, Low Birthweight, Child Stunting, Undernourishment) remain steady at 50-120 countries. One purple line (Severe Food Insecurity) dramatically rises from 35 countries in 2016 to 60 in 2022, with a gray shaded box highlighting the post-2016 period.

📊 #TidyTuesday – 2025 W41 | World Food Day
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#rstats | #r4ds | #dataviz | #ggplot2

13.10.2025 22:17 — 👍 7    🔁 0    💬 0    📌 0
Bar chart comparing EuroLeague basketball success by country. Greece leads with 27 Final Four appearances and 10 titles, followed by Spain (12 appearances, 6 titles) and Turkey (12 appearances, 4 titles). Seven other countries have 1-4 Final Four appearances each. Greece's 37% title conversion rate is noted.

Bar chart comparing EuroLeague basketball success by country. Greece leads with 27 Final Four appearances and 10 titles, followed by Spain (12 appearances, 6 titles) and Turkey (12 appearances, 4 titles). Seven other countries have 1-4 Final Four appearances each. Greece's 37% title conversion rate is noted.

📊 #TidyTuesday – 2025 W40 | EuroLeague Basketball
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#rstats | #r4ds | #dataviz | #ggplot2

06.10.2025 00:18 — 👍 5    🔁 0    💬 0    📌 0
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%.

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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#SWDchallenge | #dataviz | #rstats | #ggplot2 | #DataStorytelling

01.10.2025 13:48 — 👍 2    🔁 0    💬 0    📌 0
Two-panel chart showing Lake Hornborgasjön crane observations from 1994 to 2024. The top panel displays seasonal patterns with spring migration (blue, peaking around 10,000 cranes in April) significantly higher than fall migration (orange, peaking around 9,000 in October). The bottom panel shows cumulative annual observations, colored from purple (1990s) to orange (2020s), demonstrating population growth from approximately 77,000 cranes in 1994 to over 427,000 in 2024, a more than threefold increase over 30 years.

Two-panel chart showing Lake Hornborgasjön crane observations from 1994 to 2024. The top panel displays seasonal patterns with spring migration (blue, peaking around 10,000 cranes in April) significantly higher than fall migration (orange, peaking around 9,000 in October). The bottom panel shows cumulative annual observations, colored from purple (1990s) to orange (2020s), demonstrating population growth from approximately 77,000 cranes in 1994 to over 427,000 in 2024, a more than threefold increase over 30 years.

📊 #TidyTuesday – 2025 W39 | Crane Observations at Lake Hornborgasjön, Sweden (1994–2024)
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#rstats | #r4ds | #dataviz | #ggplot2

29.09.2025 22:23 — 👍 7    🔁 0    💬 0    📌 0
Post image

Thank you for catching the legend error - now fixed! You're absolutely right about share vs absolute spending inequality. The chart focuses on budget allocation patterns across income groups.

24.09.2025 17:44 — 👍 6    🔁 0    💬 0    📌 0
Two-panel chart showing UK household spending inequality by income in 2024. The left panel displays spending gaps between the poorest and wealthiest households across 11 categories, with housing showing the most significant gap at 19.6 percentage points. The right panel shows distribution patterns across all five income quintiles using ridge plots. Housing costs disproportionately burden poor households, while transport spending favors wealthy households.

Two-panel chart showing UK household spending inequality by income in 2024. The left panel displays spending gaps between the poorest and wealthiest households across 11 categories, with housing showing the most significant gap at 19.6 percentage points. The right panel shows distribution patterns across all five income quintiles using ridge plots. Housing costs disproportionately burden poor households, while transport spending favors wealthy households.

📊 #MakeoverMonday – 2025 W39 | Family spending in the UK
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#rstats | #DataFam | #dataviz | #ggplot2

24.09.2025 09:03 — 👍 23    🔁 1    💬 5    📌 0
Multi-panel visualization showing chess player activity and achievements from FIDE data (August-September 2025). The top panel displays four histograms of game activity levels, showing that most players are casual (1-3 games) while fewer are highly active (16+ games). Bottom left shows top 20 rating improvements, led by Plzak, David, with +362 points, with a median of 255.5. Bottom right shows countries with the most titled players, led by Germany (1,004), Spain (702), and Russia (469), with a median of 391 players.

Multi-panel visualization showing chess player activity and achievements from FIDE data (August-September 2025). The top panel displays four histograms of game activity levels, showing that most players are casual (1-3 games) while fewer are highly active (16+ games). Bottom left shows top 20 rating improvements, led by Plzak, David, with +362 points, with a median of 255.5. Bottom right shows countries with the most titled players, led by Germany (1,004), Spain (702), and Russia (469), with a median of 391 players.

📊 #TidyTuesday – 2025 W38 | FIDE Chess Player Ratings
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#rstats | #r4ds | #dataviz | #ggplot2

21.09.2025 15:48 — 👍 4    🔁 1    💬 0    📌 0
Preview
Which ‘kidult’ hobbies and practices do Britons think are really for children? | YouGov Most Britons see cartoons and Disney as being for children, but tend to see Doctor Who and theme parks as being as much for adults as kids

Unfortunately, the article does not specify which Disney films are considered childish. The data in the chart shared, and the corresponding YouGov article, only refers to "Disney Films" as a general category. You can find the full article here: yougov.co.uk/society/arti...

16.09.2025 17:05 — 👍 1    🔁 0    💬 0    📌 0
Diverging bar chart showing generational differences in viewing activities as childish. Comic Books have the largest gap at +28 percentage points, with older adults more likely to see it as childish. Most activities follow this pattern, but Star Wars (-3 pts) and Disney Films (-6 pts) diverge in the opposite direction, with younger people more likely to view them as childish than older adults.

Diverging bar chart showing generational differences in viewing activities as childish. Comic Books have the largest gap at +28 percentage points, with older adults more likely to see it as childish. Most activities follow this pattern, but Star Wars (-3 pts) and Disney Films (-6 pts) diverge in the opposite direction, with younger people more likely to view them as childish than older adults.

📊 #MakeoverMonday – 2025 W38 | Which ‘kidult’ hobbies do Britons think are for children?
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#rstats | #DataFam | #dataviz | #ggplot2

16.09.2025 11:23 — 👍 3    🔁 0    💬 1    📌 0
Heat map showing recipe ratings by complexity, with cooking time on y-axis (≤30 min to 4+ hours) and ingredient count on x-axis (1-5 to 20+ ingredients). Color scale from dark blue (4.45 rating) to light green (4.63 rating) reveals higher ratings for recipes with more ingredients and longer cooking times. Each cell shows the average rating and recipe count from 14,426 AllRecipes.com recipes.

Heat map showing recipe ratings by complexity, with cooking time on y-axis (≤30 min to 4+ hours) and ingredient count on x-axis (1-5 to 20+ ingredients). Color scale from dark blue (4.45 rating) to light green (4.63 rating) reveals higher ratings for recipes with more ingredients and longer cooking times. Each cell shows the average rating and recipe count from 14,426 AllRecipes.com recipes.

📊 #TidyTuesday – 2025 W37 | Allrecipes
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#rstats | #r4ds | #dataviz | #ggplot2

14.09.2025 15:12 — 👍 10    🔁 2    💬 2    📌 0
Two-panel chart showing AI's job market impact from 2024 to 2030. The top panel displays a slope chart with IT jobs growing from 18.3M to 18.8M (green line) and Transportation declining from 18.8M to 18.3M (red line), with other industries in gray background lines. Bottom panel shows waterfall chart demonstrating cumulative job changes by sector, starting with Transportation's -444K loss, followed by smaller losses in Education (-93K) and Manufacturing (-12K), then gains in Finance (+39K), Retail (+221K), Entertainment (+387K), Healthcare (+403K), and IT (+512K), resulting in net positive job creation. The chart indicates that the data is synthetic, modeling AI adoption scenarios.

Two-panel chart showing AI's job market impact from 2024 to 2030. The top panel displays a slope chart with IT jobs growing from 18.3M to 18.8M (green line) and Transportation declining from 18.8M to 18.3M (red line), with other industries in gray background lines. Bottom panel shows waterfall chart demonstrating cumulative job changes by sector, starting with Transportation's -444K loss, followed by smaller losses in Education (-93K) and Manufacturing (-12K), then gains in Finance (+39K), Retail (+221K), Entertainment (+387K), Healthcare (+403K), and IT (+512K), resulting in net positive job creation. The chart indicates that the data is synthetic, modeling AI adoption scenarios.

📊 #MakeoverMonday – 2025 W37 | AI Impact on Job Market: (2024–2030) | ⚠️ Synthetic data
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#rstats | #DataFam | #dataviz | #ggplot2

09.09.2025 21:08 — 👍 1    🔁 0    💬 0    📌 0
Two-panel chart showing global passport power inequality in 2024. Top panel: horizontal bar chart displaying regional differences from global median visa-free access, with Europe leading at +91 destinations above the median, followed by the Caribbean (+53) and the Americas (+44), while Africa (-36), Asia (-31), and the Middle East (-27) fall below the median. Bottom panel: stacked horizontal bar chart showing regional composition by performance tiers, revealing Europe has 29 Global Elite countries and 7 Strong Performers. In comparison, Africa is dominated by 43 Emerging Markets countries and 8 Restricted Access countries. Charts demonstrate Europe's passport dominance, alongside significant disadvantages in Africa, Asia, and the Middle East.

Two-panel chart showing global passport power inequality in 2024. Top panel: horizontal bar chart displaying regional differences from global median visa-free access, with Europe leading at +91 destinations above the median, followed by the Caribbean (+53) and the Americas (+44), while Africa (-36), Asia (-31), and the Middle East (-27) fall below the median. Bottom panel: stacked horizontal bar chart showing regional composition by performance tiers, revealing Europe has 29 Global Elite countries and 7 Strong Performers. In comparison, Africa is dominated by 43 Emerging Markets countries and 8 Restricted Access countries. Charts demonstrate Europe's passport dominance, alongside significant disadvantages in Africa, Asia, and the Middle East.

📊 #TidyTuesday – 2025 W36 | Henley Passport Index Data
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#rstats | #r4ds | #dataviz | #ggplot2

08.09.2025 22:14 — 👍 9    🔁 1    💬 0    📌 0
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.

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.

Post image

📊 #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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#SWDchallenge | #dataviz | #rstats | #shiny | #dashboarddesign

03.09.2025 22:31 — 👍 3    🔁 0    💬 0    📌 0
Horizontal diverging bar chart ranking UK drug harms. Alcohol leads with the highest total harm (72 points), showing massive social harm (46.1) but moderate user harm (25.8). Heroin and crack cocaine follow, with higher user harm but lower social impact. Chart reveals disconnect between legal status and evidence-based harm - legal drugs, alcohol, and tobacco rank high, while many illegal drugs like LSD and mushrooms show minimal harm scores. Based on a 2010 Lancet study using multicriteria analysis of 16 harm factors.

Horizontal diverging bar chart ranking UK drug harms. Alcohol leads with the highest total harm (72 points), showing massive social harm (46.1) but moderate user harm (25.8). Heroin and crack cocaine follow, with higher user harm but lower social impact. Chart reveals disconnect between legal status and evidence-based harm - legal drugs, alcohol, and tobacco rank high, while many illegal drugs like LSD and mushrooms show minimal harm scores. Based on a 2010 Lancet study using multicriteria analysis of 16 harm factors.

📊 #MakeoverMonday – 2025 W36 | Drug Harms in the UK
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#rstats | #DataFam | #dataviz | #ggplot2

02.09.2025 21:00 — 👍 3    🔁 0    💬 0    📌 0
Beeswarm plot showing seasonal patterns of frog calling in Australia. Each colored dot represents the recording frequency of a single species, grouped by season (from Summer to Spring) on the y-axis and on a log-scale on the x-axis. White circles mark seasonal medians. Spring shows the highest activity with 81 species and 60,405 recordings, while Winter shows the lowest with 78 species and 32,002 recordings. Colors distinguish five major frog subfamilies (Hylid, Microhylidae, Myobatrachid, Toad, and Unknown), revealing diverse seasonal preferences within these taxonomic groups.

Beeswarm plot showing seasonal patterns of frog calling in Australia. Each colored dot represents the recording frequency of a single species, grouped by season (from Summer to Spring) on the y-axis and on a log-scale on the x-axis. White circles mark seasonal medians. Spring shows the highest activity with 81 species and 60,405 recordings, while Winter shows the lowest with 78 species and 32,002 recordings. Colors distinguish five major frog subfamilies (Hylid, Microhylidae, Myobatrachid, Toad, and Unknown), revealing diverse seasonal preferences within these taxonomic groups.

📊 #TidyTuesday – 2025 W35 | Australian Frogs
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#rstats | #r4ds | #dataviz | #ggplot2

01.09.2025 00:14 — 👍 14    🔁 2    💬 1    📌 0
Two-panel chart analyzing global meat production. The top panel displays regional trends from 1961 to 2023, featuring line graphs for six regions (Asia, North America, Europe, South America, Africa, and Oceania). This reveals Asia's dramatic growth in pig and poultry production, reaching over 60 million tonnes, while the other regions remain relatively flat. The bottom panel displays 2010-2023 statistical confidence intervals using dot plots with error bars across four meat types (Poultry, Pig, Beef & Buffalo, and Sheep & Goat), confirming Asia's dominance in most categories, with North America leading in beef production. Color coding is consistent throughout: brown for beef, bright pink for pig, orange for poultry, and green for sheep.

Two-panel chart analyzing global meat production. The top panel displays regional trends from 1961 to 2023, featuring line graphs for six regions (Asia, North America, Europe, South America, Africa, and Oceania). This reveals Asia's dramatic growth in pig and poultry production, reaching over 60 million tonnes, while the other regions remain relatively flat. The bottom panel displays 2010-2023 statistical confidence intervals using dot plots with error bars across four meat types (Poultry, Pig, Beef & Buffalo, and Sheep & Goat), confirming Asia's dominance in most categories, with North America leading in beef production. Color coding is consistent throughout: brown for beef, bright pink for pig, orange for poultry, and green for sheep.

📊 #MakeoverMonday – 2025 W35 | Meat Production by Livestock Type
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #DataFam | #dataviz | #ggplot2

26.08.2025 13:56 — 👍 4    🔁 1    💬 0    📌 0
Two-panel chart illustrating the evolution of Latin music on the Billboard charts from 1995 to 2022. The top timeline shows major hits, including "Despacito" (16 weeks) and "Macarena" (14 weeks), as peaks. Bottom-faceted bar charts display the top songs across five cultural waves: Dance Revolution (Macarena), Latin Pop Wave (Ricky Martin, Jennifer Lopez), Crossover Success (Santana), Streaming Era (Despacito), and Urban Takeover (Cardi B). Data demonstrates Latin music's progression from novelty hits to mainstream dominance.

Two-panel chart illustrating the evolution of Latin music on the Billboard charts from 1995 to 2022. The top timeline shows major hits, including "Despacito" (16 weeks) and "Macarena" (14 weeks), as peaks. Bottom-faceted bar charts display the top songs across five cultural waves: Dance Revolution (Macarena), Latin Pop Wave (Ricky Martin, Jennifer Lopez), Crossover Success (Santana), Streaming Era (Despacito), and Urban Takeover (Cardi B). Data demonstrates Latin music's progression from novelty hits to mainstream dominance.

📊 #TidyTuesday – 2025 W34 | Billboard Hot 100 Number Ones
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #r4ds | #dataviz | #ggplot2

25.08.2025 23:45 — 👍 9    🔁 2    💬 0    📌 0
Two-panel chart showing UK unemployment volatility from 1975-2025. Top panel: Bar chart of year-over-year unemployment changes by decade, with orange bars showing rising unemployment and blue bars showing falling unemployment. The largest spikes occur during the 1980s Thatcher Era and the 2008 financial crisis. Bottom panel: Dumbbell chart showing unemployment ranges by decade, with the 1980s having the highest volatility (5.7% to 11.9% range) and the 1970s the most stable (3.4% to 5.7% range).

Two-panel chart showing UK unemployment volatility from 1975-2025. Top panel: Bar chart of year-over-year unemployment changes by decade, with orange bars showing rising unemployment and blue bars showing falling unemployment. The largest spikes occur during the 1980s Thatcher Era and the 2008 financial crisis. Bottom panel: Dumbbell chart showing unemployment ranges by decade, with the 1980s having the highest volatility (5.7% to 11.9% range) and the 1970s the most stable (3.4% to 5.7% range).

📊 #MakeoverMonday – 2025 W34 | UK Unemployment Rate
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #DataFam | #dataviz | #ggplot2

19.08.2025 21:46 — 👍 7    🔁 0    💬 0    📌 0
Population pyramid showing height distribution of Scottish Munros vs Munro Tops in 2021. Green bars (right) represent 282 Munros, brown bars (left) represent 226 Munro Tops. The chart reveals that Munros dominate higher elevations above 1100m, while Munro Tops are more prevalent in lower ranges. The largest groups are found at elevations of 950-1000m (78 Munros, 73 Munro Tops) and 900-950m (68 Munros, 71 Munro Tops), indicating a relatively even distribution at lower elevations.

Population pyramid showing height distribution of Scottish Munros vs Munro Tops in 2021. Green bars (right) represent 282 Munros, brown bars (left) represent 226 Munro Tops. The chart reveals that Munros dominate higher elevations above 1100m, while Munro Tops are more prevalent in lower ranges. The largest groups are found at elevations of 950-1000m (78 Munros, 73 Munro Tops) and 900-950m (68 Munros, 71 Munro Tops), indicating a relatively even distribution at lower elevations.

📊 #TidyTuesday – 2025 W33 | Scottish Munros
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #r4ds | #dataviz | #ggplot2

18.08.2025 22:00 — 👍 8    🔁 1    💬 0    📌 1

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