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IAmSciComm | @jschwabish @policyviz

27 Feb, 11 tweets, 11 min read

Earlier in the week, I promised I'd put together a list of my favorite #dataviz tools. 🛠

These are by no means the only tools out there, but these are the ones I like and use regularly.

(Sigh, another thread....I know, I know....) 🧵

1. Excel. Yep, I use Excel for much of my #dataviz work. Excel is based on bars, lines, and dots, all in an X-Y space. Think of it that way, and you can create lots of stuff.

You can learn more in my step-by-step ebook: policyviz.com/product/a-guid…

@hadleywickham

2. #Rstats. If you code in SAS, Stata, SPSS, or other statistical packages, you won't have a hard time picking up #Rstats. Some great resources:
-r4ds.had.co.nz from @hadleywickham
-cedricscherer.com from @CedScherer
-r-graph-gallery.com from @R_Graph_Gallery

@urbaninstitute

Also check out this blog post I wrote with my @urbaninstitute colleague @awunderground on how he helped me to learn #Rstats. | urban-institute.medium.com/learning-r-a-c…

@tableau

3. @tableau. One of the leading dashboarding tools out there. There are too many resources to list--it has a great community--but I'd start with the #MakeoverMonday project led by @TriMyData.

4. #PowerBI. Another popular dashboarding tool and based within the Microsoft ecosystem. I find this being used a lot in small orgs and state/local government agencies, likely because it's pretty cheap and directly links to Excel.

@Datawrapper

5. @Datawrapper. One of the (many) browser-based #dataviz tools. Great chart options, awesome annotations, and they think about tables too! Check out the work from @lisacrost--her Datawrapper blog is fantastic! | datawrapper.de

@f_l_o_u_r_i_s_h

6. @f_l_o_u_r_i_s_h. Another browser-based tool and designed with small newsrooms in mind. They are very nimble and respond to current trends in the field. | flourish.studio

@rawgraphs

7. @rawgraphs. Another browser-based tool, this one open source. Was a bit limited until just a week ago when they published version 2.0. I love some of the options here. | rawgraphs.io

@mbostock

8. #D3. Pretty much every interactive #dataviz you see online is creating in D3, a JavaScript library. I am *not* a D3/JS programmer, but what people can create with D3 is amazing. Check out creator @mbostock and @d3visualization for more. Also: bl.ocks.org/mbostock

@Highcharts

There are MANY MANY others: @Highcharts, @ThePSF, @ProcessingOrg, @qlik, @infogram, @Venngage, @Esri, and so many others. @visualisingdata has a great collection you can browse here: visualisingdata.com/resources/

/end🧵

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More from @iamscicomm

IAmSciComm | @jschwabish @policyviz

@iamscicomm

28 Feb

@iamscicomm

Well, it's time for me to close out my week hosting @iamscicomm. Thanks for all of your questions and comments! I had so much fun chatting with folks from different fields and walks of life!

I'll leave you with my 5 general guidelines for creating more effective dataviz.

1. Show the Data.
Your reader can only grasp your point, argument, or story if they see the data. This doesn’t mean that all the data must be shown, but it does mean that you should highlight the values that are important to your argument.

2. Reduce the Clutter.
The use of unnecessary visual elements distracts your reader from the central data and clutters the page. Reduce/eliminate heavy tick marks, gridlines, textured gradients, too much text and labels. Focus on the data.

Read 7 tweets

IAmSciComm | @jschwabish @policyviz

@iamscicomm

27 Feb

@iamscicomm

I close out my week hosting the @iamscicomm account by sharing just a select few examples of #dataviz that don't follow the rules or templates or tried-and-true approaches. But they are beautiful and engaging and enlightening.

As you go forth and create your visualizations, continue to explore. Draw inspiration from all around you and from the amazing work these and other creators are generating.

@NadiehBremer

Be sure to check out the amazing work from @NadiehBremer like this one on words translated into English. | visualcinnamon.com/portfolio/beau…

Her site: visualcinnamon.com

Read 6 tweets

IAmSciComm | @jschwabish @policyviz

@iamscicomm

27 Feb

@benefitcost

I've written a bunch on how to create better data-rich tables. So prepare for a longish thread here. 🧵

Here's a 10-step summary of my "Ten Guidelines for Better Tables" in #BetterDataVisualizations and @benefitcost.

Before we get to the ten guidelines, recognize that just like in graphs and charts, there are a lot of pieces to tables. And, just like graphs and charts, we can control the look and design of all of these elements.

Rule 1. Offset the Heads from the Body
Make your column titles clear. Try using boldface type or lines to offset them from the numbers and text in the body of the table.

Read 13 tweets

IAmSciComm | @jschwabish @policyviz

@iamscicomm

26 Feb

Perhaps the most common #dataviz for qualitative data is the Word Cloud. ⛅️
In a word cloud, the size of each word is adjusted according to its frequency in a passage of text.

But here's the thing: The font, alignment, and color of the words in the word cloud can affect our perception of the data. Furthermore, it's hard to see the most important *concepts* in the text.

@MartiHearst

So, take the work @MartiHearst at Berkeley, who suggests breaking up the text into semantic groups before making the word cloud. | ischool.berkeley.edu/news/2019/word…

Read 4 tweets

IAmSciComm | @jschwabish @policyviz

@iamscicomm

26 Feb

We kick off today's subject of #dataviz for part-to-whole relationships and qualitative data with some of my favorite fun pie charts. I did not originally create these, and the original creators are lost to history.

Read 6 tweets

IAmSciComm | @jschwabish @policyviz

@iamscicomm

25 Feb

Flow maps are another kind of way to visualize your data. Maybe the most famous flow map is this one from Charles Joseph Minard in 1869. Tufte always touts this one as being the "best statistical chart ever made".

A quick 🧵 on the Minard map.

The famous Minard map shows 6 data values in a single view:
1. Number of troops (line thickness)
2. Distance traveled (scale)
3. Temperature (line at bottom)
4. Time (line at bottom)
5. Direction of travel (color)
6. Geography (cities, etc.)

But Tufte left out the fact that the Minard Napolean map was only one panel in a full spread. It also included the lesser-known map of Hannibal’s 218 BC march through the Alps to Rome. (This image from Ecole nationale des ponts et chaussées, which I include in my book.)

Read 4 tweets

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