Nathan Yau’s Book Data Points Pdf

[Doris Joo]

Thenext chapters provide a summary of how we build a data visualisation starting with the fundamental building blocks: title, visual cues (the data), coordinate system, scale and context elements. The visual cues are further broken down into attributes like position, length, angle, direction, shapes and so forth.

Data Points is much more a book about exploratory data visualisation then Storytelling with data, I think Yau believes that exploratory data analysis is an exercise in storytelling. The strength of this book is the wide range of examples used to illustrate the points being made through the book. The style is chatty, it is not a difficult read. It is less focussed on delivering specific lessons in making data visualisations than Storytelling with data.

I've worked as a scientist for the last 30 years, at various universities, a large home and personal care company, a startup in Liverpool called The Sensible Code Company (formerly ScraperWiki Ltd), GBG and now as a consultant in data science.

The new edition of Visualize This enriches readers with modern techniques and examples, focusing on effectively learning data visualization by exploring different data types and designing for clear communication, even for those without a formal design background. Nathan emphasizes the necessity of audience-appropriate visualizations and the selection of suitable tools, all of which have changed and evolved since the first edition of the book was published in 2011.

Nathan Yau is a renowned data visualization expert and the founder of FlowingData. With a background in statistics and a Ph.D. from UCLA, Nathan has combined his passion for data with his keen eye for design to help individuals and organizations understand and communicate complex information more effectively.

Nathan is author of the Visualize This and Data Points books that guide readers through the process of turning raw data into compelling visual stories. His expertise has been recognized and featured in numerous publications, including The New York Times, Wired, and The Guardian.

02:00.50

jschwabish

So does it is it following the same structure of the first book just ah updated for you know changes over in the field and and changes presumably in your perspective over the last decade or so.

02:52.84

Nathan

Um, focusing on like the design parts and the methods and the chart types so is framed is is with data types and so the second edition is still framed with data types and asking questions about data and answering questions.

03:42.22

Nathan

Um I Guess so like we go back if I go all the way back to when I started learning about visualization. It was um, it was about reports. It was like I was analyzing the data and I just needed to kind of make really quick charts.

03:57.43

Nathan

Put it in a report and it sort of like a second thought like an afterthought. Um, but then um I started working with personal data collection which was my dissertation topic and it was more like people were collecting data about themselves as a diary aspect to it.

04:16.80

Nathan

And it was not so much about like analyzing yourself and trying to improve yourself in some way. It was more like collect data about yourself like you would write in the diary and then go back. You know five ten years later and see yourself in that light in that way. Um, and so I designed visualization in that way.

04:36.40

Nathan

That was more like it was more contextual and it was more about like a queue to remember things that that happened later on so it was like a supplement to everything else in your life and then from there it went um.

04:53.87

Nathan

I ended up at the New York Times for a summer internship and then so that kind of like pushed me along for just it was it was only like six weeks but it kind of like spurred my thinking along and that has sort of influenced me.

06:07.60

jschwabish

Ah, some of the differences between like the static work you do and the interactive stuff you do, but just generally speaking like how do you think about communicating uncertainty to folks who you know may not have a stats background.

06:18.58

Nathan

Um, yeah I think um, yeah so I always remember when I was I was in Vegas with some friends and um as a stat student I I learned everything I could about blackjack and the probabilities.

06:55.55

Nathan

Like they would sometimes lose and they would get upset. Why did you tell me to do that when you know you you claim that the odds were in my favor if I did this so it was like this very simple so ah, uncertainty problem because.

07:11.70

Nathan

They looked at kind of like the individual data points but they had to you know extrapolate for like hundreds or thousands of of hands and so yeah, you always have to think about it long term. Um, so always I always kind of like think back to that and I guess people think.

07:50.61

Nathan

That in some way So even with demographic data. You could someone can zoom in onto their about themselves about their own groups and then they can sort of go from there and extrapolate and look at the whole entire population but they can always have that they have the anchor of themselves.

09:35.70

Nathan

And it was sort of like this translation of like powerpoint and so it was people coming from powerpoint and then making graphics for the web so it was like these really big infographics or long slide decks or slideshows.

12:25.72

Nathan

Ah, handbook written to myself because um, so it goes back to that New York Times thing and I had um before that it was all about charts for analysis and charts for exploration I had done very little for charts for presentation and communication.

12:45.10

Nathan

Um, so I to try to prepare like in retrospect is totally worthless. But I I tried to I read as many design books as I could and like with the established design visualization books as I could and when I got.

13:42.40

Nathan

What do you think is best and then try to and then and just go from there and then so there was like a bunch of tradeoffs of the technology that was involved and the people who are available the data that was available and so you kind of like take into all those tradeoffs into account and then you make something that is useful as useful as you can.

14:01.47

Nathan

And so like visualize this was trying to get past the all that big cluster of design books that I read that ended up not helping me I mean they helped me in my like original like kind of base thinking. Um, but then I like I just needed to actually do something like how do I use illustrator.

16:13.70

jschwabish

Right? right? And and what about the work that you do um for interactive. So ah for your interactive pieces. Do you. And are you working are you for those for that for that for that task that you just mentioned of playing with color and moving things around. Are you playing around with static versions in in Illustrator or is you doing are you doing all that in the code and doing it all in the browser.

17:00.67

Nathan

Like structures and visualization methods that would work and if I land on something then and I think that interaction or animation is going to make it easier to understand than I then I bring it I format the data clean it processes it.

20:47.99

Nathan

I think it like I have no plan for it because flowing data started as just sort of like a way to share things with my classmates so I was at ucla um I had to move to Buffalo after my master but I was still.

21:03.17

Nathan

Working on my Ph D So I used flowing data which was a domain name that I got ah that I had to buy that was free because I had to use the hosting and then so I started sharing things on flowing data and sending it to my classmates and then sort of kind of went there. Um so I feel like.

21:59.13

Nathan

Was learning visualization so in the very beginning it was about like learning visualization. What I wanted to do with it and how it like applied to the rest of my work and then I graduated um I finished my Ph D and then by that time flowing data was um enough.

22:17.76

Nathan

To be my my full time work. Um, so I just kept going with flowing data and that was part like part advertising part memberships at the time Actually I think it might have just been advertising I can remember Yeah I think.

22:37.71

Nathan

Yeah I think I think membership started a few years later so it was just advertising at the time and that was when independent publishers were able to get advertisers and make people it was not just Facebook and and Google Adsense um, and so by like.

31:56.86

Nathan

And so I get a lot of emails it I think I was on Reddit or dig or something and people are offended by it because I was making I made I made the mistake of using sarcasm on the internet and assuming that people would use the content.

32:34.83

Nathan

But people still got mad about it is so weird but it did match. It is like is very close like but it was more granular because I had actual data to look at and um and so like a lot of the things that people get mad about is when.

37:53.31

Nathan

And Data is not certain so if they can like figure out how to communicate that in some way or to understand it and have just have a general sense that this may or not may or may not be the actual thing it would be I think it would be more useful.

38:05.99

jschwabish

You know? yeah for sure. Well Nathan congrats on the new book looking forward to to seeing it in June and thanks, thanks for coming on the show as always it was. It was great cha with you.

Ask yourself what you want to know about your data. Then try to think of what people reading your graphs or charts will be looking for. The more specific you are, the better. Decide whether you prefer to explore and highlight the best (biggest, highest) or the worst (smallest, lowest) elements, compare specific data points, or maybe examine a trend over time.

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