Come and learn about your classmates! Data Visualization from self-introduction post

Part 1 (2019)
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Thanks, Jeremy! Processing structured (lat, log) pair is surely better than doing NLP on hundreds of posts!

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Map, based on Jeremy’s file with everyone’s location

01%20am
Screen Shot 2018-10-15 at 9.39.01 am.jpg2736×1524 387 KB

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Thanks @mrandy - I posted this on Twitter. https://twitter.com/jeremyphoward/status/1051676652772573184

I don’t know your twitter handle so couldn’t credit you, but feel free to reply there so we know who you are! :slight_smile:

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I’m going to guess that tiny little dot on Tasmania means I am presumably the only one here doing the course lol… Really interesting to see, so thanks for sharing.

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way to represent!

odd that sydney looks like #4 in Australia

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Hi Jeremy, would you mind elaborating a bit on the source of the geographic data? Are they from locating IP address? If that is the case, then I can understand why there are so few data points from China, cause they are all using VPN. :joy:

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Yeah it’s from MailChimp, where the signup form was. So based on IP address. Sorry for failing to properly account for 中国! 哈哈

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How can I access the file? Wanted to do some more analysis. Thanks.

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Here is the raw data.

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And here’s the India specific data. If anybody wants any other data, will be happy to share.

Course%20Distribution-India
Course Distribution-India.png1375×799 269 KB

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Here’s another go at a dataviz, using the latitude and longitude data from Jeremy in pastebin.

https://public.tableau.com/profile/alison.davey#!/vizhome/fast_aiPart1v3/Sheet2

The breakdown of participants by sub-region is:

Sub-Region
Northern America 806
Southern Asia 725
Western Europe 237
Eastern Europe 168
Northern Europe 165
South-eastern Asia 126
Sub-Saharan Africa 93
Latin America and the Caribbean 85
Australia and New Zealand 81
Eastern Asia 74
Southern Europe 66
Northern Africa 46
Western Asia 44
Central Asia 5
Total 2721
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Guys, that settles it. We need someone to move to Antarctica to take the course.

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Well, we need to first find an IP address that is located in Antarctica.

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Hey Alison, the map looks awesome. Would you mind sharing the Tableau workout with the class? I would love to learn how to make a map as good as this one.

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Hi George

Thanks, I’m thrilled that you like the map.

The data preparation was more challenging than the Tableau part. I have put everything into a notebook https://nbviewer.jupyter.org/gist/AlisonDavey/bef98362f4e442b340ed0a05ead43b91

You can also download the Tableau workbook from the web page.

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Thanks @AlisonDavey! FYI, here’s the best way I know to share notebooks like that: https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/nbextensions/gist_it/readme.html

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Cool, I’ve updated the link. Thanks.

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Very cool. Do you have a twitter handle so I can credit this work @AlisonDavey ?

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Sure, it’s @Data_sigh

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Thanks! I will look into it right now!