This week the objective was to work with time series data and find an effective way to present information relating to fuel prices in the UK.
For week 16 we asked the community to visualize greenhouse gas emissions for different food products across the supply chain.
The age old debate of Lionel Messi vs. Cristiano Ronaldo was reopened for Makeover Monday this week. Did anyone conclusively prove who the better player is? No, but there was some good variety with how people chose to present a fairly limited dataset.
In week 14, we tackled another Gender Inequality dataset in collaboration with Operation Fistula for #Viz5, looking at unpaid work and the gender disparities between how much paid and unpaid work is done.
Clearly the answer is “no – pineapple doesn’t belong anywhere near a pizza”. We all know that, but how did the #MakeoverMonday community choose to redesign the dubious YouGov original?
In week 12, our community tackled a dataset about courses offered at California University since 1900, looking at number of courses by field and area.
For week 11 of 2020 we explored data shared on Our World in Data exploring a possible link between GDP per Capita and self-reported Life Satisfaction
Week 10 kicked off our Visualize Gender Equality campaign #Viz5 with the topic of attitudes on violence towards women and girls. Check out this week’s favourites to learn more.
Rodrigo Calloni shared the data for the ninth week of Makeover Monday in 2020. How did the community approach improving upon a simple data table?
For week 8 #MakeoverMonday collaborated with the Australian Institute of Housing and Wellbeing to visualize the outcomes of homlessness services.
Andy Kriebel supplied data this week via Credit Suisse showing the distribution of World Wealth. There was a great variety to the submissions this week – check out the favourites!
In week 6 we looked at the US involvement in wars and how that translates into young people’s experience of growing up in a country that has never been at peace in their lifetime.
The challenge in week five was to frame some data relating to James Bond from both sides of the Brexit divide
For week 4 we collaborated with Bridges for Prosperity to highlight the great work they are doing across the world. Check out this week’s favorites showing where bridges have connected people and improved their quality of life.
For the third data set of 2020, we set the task of visualising data about the consumption of “free sugars” in the UK
For week 2 we asked the community to tackle a dataset about pesticide use in the US versus other major agricultural producers.
For Charlie’s first Makeover Monday dataset, he looked at how sports favourability has changed over time in America
Original visualization | Data set on data.world FAVORITESAuthor: Brett GrodzitskyAuthors: Adam Crahen / Pooja GandhiAuthor: Marian EerensAuthor: Ian Conlon Author: Shawn Levin Author: Andreas KoschinekAuthor: Chantilly JaggernauthAuthor: Kate Schaub
During Christmas week we challenged Makeover Monday participants to visualize how much money is spent by Brits and Europeans for Christmas.
Original visualization | Data set on data.world | Viz Review Webinar FAVORITESAuthor: Joakim DalenAuthor: Takafumi ShukuyaAuthor: Klaus SchulteAuthor: Candra McRaeAuthor: Tushar MoreAuthor: Meera UmasankarAuthor: Bo McCreadyAuthor: Evelina JudeikytėAuthor: Ryan...
For week 50 we analyzed the revenue and number of stores of the top 30 fast food chains in the US. The results may surprise you. Check out this week’s favorites…
Original visualization | Data set on data.world | Viz Review Webinar FAVORITESAuthor: Candra McRaeAuthor: Barnabas Markus Author: Evelina Judeikytė Author: Philippe Massicotte Author: Agata Ketterick Author: Yanning Wang Author: Agnieszka Atlasik Author: Tushar...
Making over data visualizations has been my primary learning method for the past 10+ years. My first blog post was a simple makeover of a pie chart. Before After It was nothing fancy (I didn't even know how to take a decent screenshot) and it was the start of...
As winter approaches, we look at data from the Squirrel Census about NYC Central Park squirrel numbers, fur colors and behaviours. Check out this week’s favorites for a look at different visualizations of the data.
Our first challenge post-TC19 was to visualize the change in smartphone ownership in tweens and teens between 2015 and 2019. Check out the favorites!
Week 46 saw 1600 people create #MakeoverMonday vizzes on Literacy rates during #data19 in Las Vegas. Here are this week’s favorites.
#MakeoverMonday week 45 was all about getting everyone fired up for TC19. They had to visualize visitors and convention attendees in Las Vegas. Check out the favorites.
Before winter consumes much of the Nothern Hemisphere with longer hours of darkness, we challenged everyone to visualize the hours of sunshine enjoyed by different cities around the world.
CONTENT WARNING: death, suicide • For #MakeoverMonday, the community brought to light a very difficult topic: suicide. Here are the vizzes that communicated the topic most effectively.
In week 42 #MakeoverMonday was all about the Ironman World Championships in Hawaii and the medal winners from 1978 to 2019. Check out this week’s favourites from nine different participants.
Here are the favorites for week 41, in which we visualized donations accepted by UK political parties. Some interesting analysis!
Is London getting older? Will there be more old people than young people and children in the next few decades? And where do the older versus younger generations live? These questions were tackled by the community for week 40 of Makeover Monday, looking at population predictions for England’s capital city.
For #MakeoverMonday week 39, the community visualized evictions in San Francisco.
Week 38: Positive Impact Events – Commitments from the Event Industry for the Sustainable Development Goals
Week 38 challenged our community to tackle survey data from MyWorld2030 to gain insights into the committments of the events industry to take action towards the SDGs. This collaboration is in support of the SDG Action Campaign.
For week 37, we analyzed which books fans of James Patterson checkout from Seattle’s public libraries.
During week 36 the #MakeoverMonday community worked with survey data on the seasons preferred by Americans.
The future of gaming was the topic for week 35. Who created the vizzes I liked this most?
In week 34 we asked our Makeover Monday community to visualize survey data about how attached teens and their parents are to their mobile phones and the impact it has.
For week 33 we challenged the community to visualise an in-depth dataset about clinical trials by leading drug companies.
In week 32 the community analysed UK Gridwatch data to showcase Britains phasing out of coal-powered energy.
Following on from week 29’s theme about frequency of sex in America, this week the Community visualized data about STDs in America.
For week 30, to celebrate Andy’s 800th Tableau Public viz, Eva challenged the community to visualize Arsenal FC’s 2018/19 season.
Some people might have thought week 29 was a sensitive topic. This week, we challenged the community to visualize the declining frequency of sex in America.
During week 28, we challenged our community to visualize how asylum application numbers to Europe have changed over the last 10 years.
For week 27, David Murphy asked us to makeover a viz he created with his personally collected data about deaths in Game of Thrones. Check out his favorites for the week.
For week 26 we tackled the topic of alcohol consumption. The community created many makeovers of a simple bar chart from World Atlas. Check out this week’s favorites here.
Week 25 was a #MakeoverMonday Live at TC Europe looking at Airbnb listings and reviews in Berlin
For week 24 we celebrated #PrideMonth with data and asked the community to tackle a dataset about attitudes towards same-sex relationships. Here are this week’s favorites.
Are Americans sleeping more or less? Check out this week’s favorites to find the answer.
In week 22 the community tackled data about CO2 emissions by countries across the globe, highlighting the severity of the situation when it comes to climate change.