Aug 5, 2024 · Here are my top 10 visualization mistakes to avoid. 1. Pie Charts. Let’s start with pie charts. Simply put, avoid using them in professional presentations. It is difficult to accurately gauge the size of pie slices — is that 5% or 10%? If you have to label them with numbers, the chart becomes cluttered and confusing.

Helping students create effective visualizations in R using ggplot2 is one of my favorite parts of being a Harvard teaching assistant. I’ve seen many visualizations, ranging from insightful...

May 31, 2023 · Bad data visualization is a visualization that can mislead or misinform the viewer. As Alberto Cairo mentioned in his paper “Graphic Lies, Misleading Visuals”, bad data visualization has the following properties. A bad visualization hides relevant data or doesn’t show much data to mislead the viewer.

Jun 9, 2021 · There are some great examples from r/crappydesign: Google “Edward Tufte chartjunk” and you’ll get some relevant results, methinks.

Jun 16, 2024 · Bad Data Visualizations can mislead viewers, distort information, and convey incorrect messages. 1. Misleading Graphs. 2. Inappropriate Chart Types. 3. Overcomplicated Visuals. 4. Lack of context. 5. Poor use of colors. Why they don't work?

Nov 16, 2015 · Why lines in a chart generated from ggplot2 on Mac looks so smooth and round, but on Windows they look so sharp and edgy. Is there any option to fix that on Windows instead of going to the Apple Store?

Jul 22, 2022 · By using a bar chart to visualise the data, it leads us to instinctively compare the bars against each other to get some perspective of differences. In this case, it seems Yang won the poll...

May 17, 2023 · It highlights how easily data visualizations can mislead, especially with distorted scales or misleading labels. The Florida gun death graph is a great example of how the axis start point can...

Apr 12, 2025 · Here are some bad data visualization examples. What's In This Guide? 1. BBC Avocado Toast Index. 2. Walt Disney’s Companies Worldwide Assets. 3. CBSN. 4. The Economist, Why ticket prices on long-haul flights have plummeted. 5. Venezuelan elections. 6. Cherry-picking. 7. ASEC Data, Household Income Percentiles. 8.

ggplot2 is a R package dedicated to data visualization. It can greatly improve the quality and aesthetics of your graphics, and will make you much more efficient in creating them. ggplot2 allows to build almost any type of chart. The R graph. gallery focuses on it so almost every section there starts with ggplot2 examples.