Back when I was a kid, I used to read A LOT of books. Then, over the last couple of years, movies and TV series somehow stole the thunder, and with it, my attention. I did read a few odd books here and there, but not with the same ferocity as before. I could also feel my attention span dwindling so I had trouble reading longer, slower-paced books. It was always easier to consume media to satiate my curiosity and experience something new, especially with the rise of beautiful video essays.

其他回当我还是个孩子的时候，我曾经翻阅了很多。 然后，在过去的几年中，电影和电视连续剧以某种方式偷走了雷声，并引起了我的注意。 我确实在这里和那里读了几本奇怪的书，但是没有像以前一样凶悍。 我也感到自己的注意力在减少，所以我无法阅读更长的，节奏较慢的书。 使用媒体来满足我的好奇心和体验新事物总是容易得多，尤其是随着精美视频文章的兴起。

Everything changed this year. I learned to let go of the expectation of finishing a book and go back to why I enjoyed reading them in the first place. As a consequence, I’ve read more books in the first six months of this year than I have in the last four years combined. This led me to questions about my reading patterns. How have they evolved over time? What are my favourite genres?

今年一切都变了。 我学会了放下完成一本书的期望，然后回到为什么我喜欢阅读它们的初衷。 结果，今年前六个月，我阅读的书籍比过去四年中阅读的书籍总数还要多。 这使我对我的阅读方式提出了疑问。 它们是如何随着时间演变的？ 我最喜欢的类型是什么？

I already knew these answers for movies. I’ve been on Letterboxd for a long time. For the uninitiated, Letterboxd is the better version of IMDb. It’s a site with great design, an awesome rating system, and has a great community of people who love movies and make brilliant lists. Above all of these though, the thing I love most is their stats page. A quick glance shows me that I’ve watched movies from 47 countries and my most-watched director, to my absolute dismay, is David Dhawan.

我已经知道电影的这些答案。 我已经在Letterboxd上使用很长时间了。 对于初学者来说，Letterboxd是IMDb的更好版本。 这是一个设计出色，评分系统很棒的网站，并且拥有许多人，他们热爱电影并做出出色的榜单。 最重要的是，我最喜欢的是其统计信息页面 。 一眼就看出我看过47个国家/地区的电影，而我最受瞩目的导演是大卫·达万(David Dhawan)。

I wanted something similar for books. My first stop was Goodreads but their stats page was nowhere as good as Letterboxd. I did some more research and came across The StoryGraph. It’s a new site that’s in beta but shows much promise. Each book is tagged with parameters like “mood” and “pace” of the book which they consider while giving personalised recommendations. Think of Spotify’s Echonest algorithm but for books. The nerd in me was delighted.

我想要类似的书籍。 我的第一站是Goodreads，但其统计信息页面不如Letterboxd好。 我做了更多研究，发现了StoryGraph 。 这是一个处于测试阶段的新网站，但前景广阔。 每本书都标记有参数，例如书的“心情”和“节奏”，他们在提供个性化推荐时会考虑这些参数。 考虑一下Spotify的Echonest算法，但不适合书籍。 我的书呆子很高兴。

Logging all the books I’ve read was an arduous task. I had logged some books historically on Goodreads but not the entirety of my reading history. The remaining books I logged through memory, with help of social media posts, notes, letters, old photos, birthday gifts, etc. By the end of it, I logged a paltry 168 books and imported them into The StoryGraph, which has its own stats page, which in turn gave me ideas to create new visualisations. I reached out to Nadia from The StoryGraph and she sent me a dump of all of the data that I had logged even though the feature is not open to public yet (thanks Nadia!).

记录我所读的所有书是一项艰巨的任务。 我曾经在Goodreads上记录过一些书籍，但不是我的全部阅读历史。 余下的书是我在社交媒体帖子，笔记，信件，旧照片，生日礼物等的帮助下通过记忆记录的。到最后，我记录了仅有的168本书，并将它们导入了StoryStorm，后者拥有自己的统计信息页面，这反过来给了我一些想法，以创建新的可视化效果。 我从The StoryGraph接触了Nadia，尽管该功能尚未公开，她还是向我发送了我记录的所有数据的转储(感谢Nadia！) 。

A quick word about the data. I have not logged any comics I’ve read yet. Two reasons why:

关于数据的简短说明。 我还没有记录过我读过的任何漫画。 原因有两个：

1. I’ve read too many (at least 800 issues of Batman, 300 issues of The Flash, 100 issues of Tinkle, etc.) and logging them is going to take some time.

   我读了太多书(至少800期的《蝙蝠侠》，300期的《 Flash》，100期的《 Tinkle》等)，并且记录它们将花费一些时间。

2. Secondly, this would massively skew my data so I’ve not added them as yet. I logged in almost every book I could remember reading.其次，这将严重扭曲我的数据，因此我尚未添加它们。 我登录了几乎所有我记得的书。

Also, this is not the entirety of what I’ve read. A lot of old books are not present in the Goodreads/The StoryGraph database so those I haven’t been able to log. Eventually I managed to tag all the ones I imported and came up with some rudimentary visualisations. Let’s dive in!

另外，这还不是我所读内容的全部。 Goodreads / The StoryGraph数据库中没有很多旧书，因此我无法记录这些旧书。 最终，我设法标记了所有导入的内容，并提出了一些基本的可视化效果。 让我们潜入吧！

表面潜水 (The Surface Dive)

页数 (Pages)

For the first one, I bucketed books into three: < 300 pages, 300–500 pages, 500-plus pages to see their progression over time. I started out with a lot of small books and then when I finished my board exams, I read a LOT of large books for the next couple of years. Then I started working and still read a lot of medium sized books. Over the last couple years, I’ve gone back to reading a lot of small and medium-sized books and I hope to read a large book soon.

对于第一个书，我将书籍分为三部分：<300页，300–500页，500余页，以查看它们随着时间的推移。 我从很多小书开始，然后当我完成董事会考试时，在接下来的几年里，我读了很多大书。 然后我开始工作，但仍然阅读许多中型书籍。 在过去的几年中，我已经回到阅读许多中小型书籍，并且希望很快阅读一本大书籍。

步伐 (Pace)

I then charted pace of the books I’ve read as characterized by The StoryGraph. I generally prefer fast-paced books because I need something that holds my attention. The data backs that up, showing that fast-paced books do make up the majority of what I’ve read. I think (I could be wrong) an author has to be particularly skilled to hold someone’s attention when it’s a slower-paced story.

然后，我绘制了以The StoryGraph为特色的已读书籍的进度。 通常，我更喜欢快节奏的书，因为我需要吸引我注意力的东西。 数据支持了这一点，表明快节奏的书确实构成了我所阅读的书的大部分。 我认为(可能是错误的)当故事节奏较慢时，作者必须特别熟练才能引起某人的注意。

This made me wonder: Do we have more fast-paced books now to go along with people’s dwindling attention spans? Mapping the publishing landscape would be a worthy subject for a future post, but in the meantime it’s made me consider how the evolution of publishing might impact my own reading patterns.

这让我感到奇怪： 我们现在是否有更多快节奏的书籍可以与人们日益减少的关注范围相提并论？ 绘制出版前景图将是未来文章的主题，但与此同时，这使我考虑了出版的发展可能如何影响我自己的阅读模式。

Anyway, despite my preference for faster pace, I do enjoy reading slow-paced books as well, and I was really surprised to find that almost all the books I’ve read this year are slow-paced. That wasn’t a conscious decision on my part, but could be due to another shift I uncovered in my reading habits:

无论如何，尽管我更喜欢快节奏，但我也喜欢阅读节奏慢的书，而我发现今年我几乎阅读的几乎所有书籍都是节奏慢的，我感到非常惊讶。 对于我而言，这不是一个有意识的决定，但可能是由于我在阅读习惯中发现的另一个变化：

小说 (Fiction)

Going in, I already knew the fiction/non-fiction divide. I’ve always preferred fiction and even scoffed most times at non-fiction. When I was young, non-fiction books were basically reference or self-help books. Now that we have very accessible online tutorials for anything you may want to learn, I didn’t really have the need for them. That was until I read Meggs’ History of Graphic Design in 2016. That book was a catalyst for me to see what other golden knowledge lay hidden in these books. I knew I’ve read a lot of non-fiction recently but was surprised to find that all the books I’ve read this year are non-fiction, including the book I’m currently reading. I think I got tired of watching too many video essays, so went on a knowledge rampage when the lockdown began and hence the spike.

走进去，我已经知道小说/非小说的鸿沟了。 我一直偏爱小说，甚至在大多数时候都不喜欢小说。 我小时候，非小说类书籍基本上是参考书籍或自助书籍。 现在，我们已经为您提供了非常容易访问的在线教程，您可能想要学习任何东西 ，而我实际上并不需要它们。 直到我读了Meggs的《 2016年平面设计史》 。这本书对我来说是催化剂，让我了解这些书中还隐藏着哪些其他黄金知识。 我知道我最近读过很多非小说类书籍，但惊讶地发现我今年读过的所有书籍都是非小说类书籍，包括我目前正在阅读的书籍。 我想我已经厌倦了观看过多的视频文章，所以当锁定开始并因此而激增时，就进行了一次知识横扫。

整个历史 (The Entire History)

The breakouts were cool but I wanted to see my entire history using a single visualisation. Also, since there are multiple genres of a novel, I’ve tagged each book with a “main” genre for this visualisation. This took some time since there are some books that gave me sleepless nights. Is Audrey Niffenegger’s The Time Traveller’s Wife romance, or sci-fi? How about Vikas Swarup’s Q&A? What even is Old Man and the Sea?

这次突破很酷，但我想通过一次可视化查看我的整个历史。 另外，由于小说有多种类型，因此我为每本书都标记了一种“主要”类型以进行可视化。 这花了一些时间，因为有些书使我彻夜难眠。 奥黛丽·尼芬格(Audrey Niffenegger)的《时间旅行者的妻子》是科幻小说还是科幻小说？ Vikas Swarup的问答如何？ 老人与海又是什么？

Enter the below visualisation. It looks like a sankey diagram but is spiritually a parallel sets plot (which deals more with categorical data and how it is classified). The genres on the right are ordered by appearance in which I first read them.

输入以下可视化效果。 它看起来像sankey图，但从精神上讲是一个平行集图(它更多地处理分类数据及其分类方法) 。 右边的流派是按照外观的顺序排列的，这是我第一次阅读它们时的样子。

I’ve always been a huge fan of fantasy but was very surprised that I hadn’t picked any fantasy book up until very late into my reading years.

我一直是幻想的忠实拥护者，但令我感到惊讶的是，直到我读完书的很晚才拿起幻想书。

Once I did, I was unstoppable. 2004 was entirely thriller and fantasy!

一旦做完，我就势不可挡。 2004年完全是惊悚片和幻想片！

景观 (The Landscape)

I still wanted to see all the genres I’ve read across the years so I made the titular “Landscape of Literature” for genres. The graph at the beginning of the article is exactly that, but while it looks pretty, it’s not the best for analysis, which is why the Ridgeline Plot is a better option. I’ve accounted for multiple genres of the same book in this visualisation.

我仍然想看看我多年来阅读的所有流派，所以我为这些流派制作了名义上的“文学风景”。 文章开头的图形就是这样，但是虽然看上去很漂亮，但并不是分析的最佳选择，这就是为什么Ridgeline图是更好的选择的原因。 在这种可视化中，我已经考虑了同一本书的多种风格。

Adventure was a huge theme when I began (Journey to Center of the Earth, Treasure Island) before reading a lot of mystery books (Secret Seven, Famous Five, Hardy Boys, Nancy Drew). Then graduated to fantasy (LOTR, Harry Potter). The spike of mystery, history, and thrillers starting from 2003 can be attributed to The Da Vinci Code and all the books similar to it that I read. Fantasy then makes a comeback because of A Song of Ice and Fire and continues almost through the whole decade. A big twist was Sci-Fi; for a genre that I love so much, I’ve read surprisingly few. In the last couple of years, non-fiction genres like design and business have been surging owing to a lot of reference books I’ve been reading and catching up on.

在我开始( 前往 金银岛 的地球中心之旅 )之前，冒险是一个巨大的主题，然后阅读了很多神秘书籍(《 秘密七》 ，《 名著五》 ，《 哈代男孩》 ，《 南希·德鲁》 )。 然后毕业于幻想( LOTR ， 哈利·波特 )。 从2003年开始，神秘，历史和惊险刺激的高峰可以归因于《达芬奇密码》和我所读过的所有类似书籍。 然后，幻想因《 冰与火之歌》而卷土重来，并持续了整整十年。 科幻小说是一个很大的转折。 对于我非常喜欢的一种类型，我很少读过。 在过去的几年中，由于我一直在阅读和追赶的大量参考书，诸如设计和商业之类的非小说类书籍一直在蓬勃发展。

My last visualisation deals with the moods associated with the books I’ve read. Although adventure as a genre tapered out in my childhood, almost all the books I’ve read are adventurous in spirit. The second-most prominent set are dark, mysterious, and tense books that almost increase in frequency on cue as lighthearted tapers off.

我的最后一个可视化处理与我读过的书有关的情绪。 尽管冒险作为一种流派逐渐消失在我的童年时代，但我读过的几乎所有书籍都具有冒险精神。 第二大突出的书籍是黑暗，神秘和紧张的书籍，随着轻松愉快的逐渐消退，线索的频率几乎增加了。

That’s a walk through the history of my reading so far. Feel free to linger around and dive into the data. If you have any suggestions please feel free to drop them in! You could have insights slightly different than mine so please feel free to leave them in too.

到目前为止，我已经了解了我的阅读历史。 随时徘徊并深入研究数据。 如果您有任何建议，请随时加入！ 您可能获得的见解与我的见解略有不同，因此请随时将其保留。

This was a great eye-opener for me. Some of my pre-conceived notions were broken, and I picked up on some very interesting patterns I would’ve never seen if I hadn’t visualized it. Why haven’t I read adventure books since I was a kid? Is it because there are very few true adventure books out there now or haven’t I put enough effort in finding them? This is what is great about data and why I love it. Data is a mirror you can use to reflect upon yourself and confront your biases. What you do with it is then up to you.

这让我大开眼界。 我的一些先入为主的观念被打破了，我发现了一些非常有趣的模式，如果我不可视化的话，我将永远不会看到。 为什么我从小就不读冒险书籍？ 是因为现在很少有真正的冒险书籍，还是我没有花足够的精力去寻找它们？ 这就是数据的优点，也是为什么我喜欢它。 数据是一面镜子，您可以用来反思自己和面对自己的偏见。 然后，您要做什么就取决于您。

I still have multiple improvements planned for this and more ways to dig into data — author diversity (how eurocentric is my author list?), book formats (when did I start embracing eBooks?), the difference between my “Read” and “Want to Read” lists, etc. I also want to make this a real-time dynamic page à la Letterboxd. Let’s see how I get along with that a month or two from now.

我仍然计划为此进行多项改进，并采用更多方式来挖掘数据-作者的多样性(作者列表以欧洲人为中心？) ，书籍的格式(何时开始使用电子书？) ，“阅读”和“想要”之间的区别阅读”列表等。我也想使它成为一个实时动态页面，如“带信箱”。 让我们看看从现在起一两个月后我如何相处。

My name is Nimit Shah and I’m a designer, coder, and data guy who loves integrating the three in interesting ways. This article first appeared on my website (supports dark mode and has an interactive chart!). The code for ridgeplot and the parallel sets can be found on Observable.

我的名字叫Nimit Shah，我是一名设计师，编码员和数据专家，喜欢以有趣的方式集成这三个工具。 这篇文章首次出现在 我的网站上 (支持暗模式并具有交互式图表！)。 可以在 Observable 上找到 ridgeplot 和 并行集 的代码 。