Discover and read the best of Twitter Threads about #Visualisations

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Want to take your #Visualisations to the next level? Here are some top tips for getting started as well as some design thoughts to consider.
@TPP_SystmOne
#Gavin

1/6
1. Plan it out
Seems pretty obvious doesn't it, but with a few different design options it makes sense to think about which layout to use.
What is going to sit where on the page?
Make sure that the right information is visible to the user in the right order.

2/6
2. Choose your colours carefully!

The more mellow the colours you choose, the easier on the eye for the user. You can also be clever with the way that you then utilise colour. For example, anything displaying allergies or sensitivities can show in red.

3/6
Read 6 tweets
Many years ago my then employer @Teradata let me create a set of #Analytics cards. @JudyBayer and @edouardss helped hone them.

So here's a thread that some of you in #DataScience might find useful.

1/n
The idea was simple. If you are doing some cool Data Science every now and then just draw a card, and see if you can answer it for your project. If not... well.

2/n
So over the next 52 days (plus Joker days) I'm going to draw a card and explain why it's important. At #random. Because in data random is usually best.

3/n
Read 71 tweets
Last day with me @helenajambor on #sciviz #visualisations. Today to wrap up let's briefly discuss color and layout.
In 3 scenarios we use color. 1) to give a naturalistic representation in drawings and photos. But "natural" colors in charts quickly get awkward: it is frowned upon to use blue/boys, pink/girls color code. Also avoiding a certain color-code can be tricky, see Pew research example
2) color encodes quantities. In a heat map cells are colored by value, in microscopy images false-colours show protein enrichments, in scatterplots saturation of dots in colored to show a third observation.
Read 16 tweets

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