Thread by @annapurani93

Thread 🧵-

Creating a good #dataviz with the right colours might seem like a herculean task, but it's not.

So, here are six pointers that might help ease your process. Follow along 🤗

#datafam #DataAnalytics #RStats #DataScience

1. Use as few colours as possible to convey your idea - try & look for means to group your variables in such a way that fewer colours can be used to convey your point better.
Eg: Top N products in one colour & the others in another, instead of one colour for each product

2. Use gray in your chart - it is strong enough to be distinguished from white so your variable won't blend into the background, and you can easily combine it with a stronger colour like red if you want to show contrast or highlight another variable

#datafam #dataviz #Rstats

3. Speaking of contrast, use contrasting colours (red and blue, for example) when you're using diverging variables. Use a sequential palette (various shades of blue) when you're charting different magnitudes of the same variable

#RStats #dataviz #DataScience #DataAnalytics

4. Less is more in #dataviz. Cut off variables that don't add value to the story. Retain only those dimensions - however few - that drive your point home. This way, you're also reducing the number of colors you'll be adding to your chart

#DataAnalytics #DataScience #datafam

5. Don't add colour to text unless it's a straight replacement for the legends. Keep the text in a common, clear, readable colour across your dashboard

#rstats #DataAnalytics #DataScience #dataviz #datafam

6. Keep the colour-blind folks in mind while choosing your palette. Your visualization is pointless if it isn't accessible

If there are other pointers you follow while creating a #dataviz, do add to this 🧵

Cheers!

#Rstats #datafam #tidyverse #DataAnalytics #DataScience