This week the #MakeoverMonday challenge consisted of visualizing a dataset about US GDP by counties. Check out the maps, bar charts, line charts and dashboards in this week’s favorites.
For week 39 we tackled another #Viz5 dataset, this time about child marriage. Our #MakeoverMonday community did a great job working with data about such a difficult topic and handled it with care and consideration. Check out this week’s favorites here!
Week 38 came with lots of submissions from the community, visualizing the price index of books and all other consumer goods for various countries. Check out this blog post for a video containing the lessons learned and this week’s favorites.
The data this week reflected a decade of aggregated teacher salary data from England. The #MakeoverMonday community did a great job of clearly and concisely representing this in an effective way.
A great variety of vizzes was created to visualize the nutritional value of different breakfast cereals. Check out the video to hear this week’s lessons and see Eva’s favorites.
Join us for MakeoverMonday Live(ish) on October 5th to analyze and visualize together with thousands of people around the globe. We’ll bring the live event right into your home office and we’d love to have you join us
Who would have thought that such a small dataset could incite such debate during Viz Review?! Lots of people were taken out of their comfort zone this week, and that’s a good thing. Lots of submissions were peppered with distracting icons and images; chart junk. In most cases, simplicity is best so the main lesson from this week for me is: if it doesn’t add to the understanding of the data, don’t add it to the visualisation!
For week 34 the community tackled another #Viz5 challenge to analyze and visualize data about women’s access to contraception in low and low-middle income countries. Check out the favorites for this week.
To tie in with his trip North of the border, Charlie shared some data related to tech companies based in Scotland. Do you always need to use maps when geographic data is provided? Maybe, maybe not. When executed well it certainly adds some flourish to a data viz.
During week 32 the community visualised the benefits of working from home. Check out the great charts and dashboards they created.
The #MakeoverMonday community tackled a fairly bland dataset with customary gusto this week. Here is a selection of the favourites this week.
For this #MakeoverMonday and #Viz5 challenge the community visualized the proportion of women in parliaments around the world. Check out this week’s favorites here.
Simple survey data this week and the challenge was as much about tone of voice and objectiveness as it was about data visualisation. It’s one thing to be able to present data in a captivating way. but understanding how to describe and position your wording is as important.
During week 28, the #MakeoverMonday community worked with data collected by scientists at Palmer Station, Antarctica. The data covers three different penguin species and some of their physical attributes.
This week we looked at data from 2014 via NHS Digital looking at self-reported symptoms of common mental health disorder. The challenge was as much the use of language and understanding of the limitations of the data, as it was to present it in a clear and effective way.
For week 26, the #MakeoverMonday community worked on another #Viz5 challenge, visualizing economic empowerment data. Check out this week’s favorites here.
Amazon post modest profit margins each quarter. Take a look to see the ways in which members of the #MakeoverMonday community presented that data in week 25 of the 2020 datasets
The #MakeoverMonday worked on high school sports participation rates for week 24, showing the increasing popularity of soccer among girls.
Attitudes to meat-free and animal-free foods in Great Britain came under the microscope in week 23. How many ways can survey results be visualised? Well, at least six!
During week 22, the MakeoverMonday community tackled the challenging topic of FGM, female genital mutilation, to raise awareness for charities striving to put an end to the practice in Tanzania.
An exceptional week of submissions this week, where the majority were subtle variations on a solid original visualisation. A reminder to all #MakeoverMonday participants: favourites can only be selected from Twitter submissions including a static screenshot of the final visualisation; we can’t incorporate .gifs in the Favourites post so they won’t be included.
In week 20 the #MakeoverMonday community tackled a dataset about car insurance rates in the US in 2020, highlighting rates for minimum and full cover.
The task this week was to try to improve upon a stacked bar chart representing metrics related to the 2020 World Happiness Report. There was a lot of variety in the submissions this week, which is reflected in the favourites. There were many, many more which came close!
During week 18 we tackled another #Viz5 dataset. This month the topic was obstetric fistula in Madagascar, with a detailed dataset provided by Operation Fistula. Check out this week’s favorites here.
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.