Trakt.telly is a great, gratis service for tracking your Tv and movie watching. You tin can manually log what you lookout man or use additional integrations and tools to automatically rails everything on Netflix and other places.

Whether your goal is to decrease your TV addiction or mere curiosity at knowing which shows yous scout and when, Trakt is one of the best ways to quantify your media consumption. I've written previously almost how rails your Tv set and movie watching using Trakt. Personally my chief usage is seeing my weekly viewing time statistic, which I tin can employ in my data-driven weekly review equally a data point to better judge how much tube time I spent and, if excessive, potentially take action.

Permit's go one footstep beyond the bodily tracking and start leveraging our information. But first things first is getting our data.

Tracking services that don't allow you to export your data should be avoided and honestly take a very bad data policy. Fortunately, Trakt provides a few options to export your data. One option is to become a VIP premium member and to download a CSV consign directly from Trakt.boob tube. Alternatively, you can use a data aggregation service called Zenobase to pull your watching history direct from Trakt.

In this post, we will look at how to consign your data from Trakt using Zenobase. First, we will look at how to integrate Trakt with Zenobase; 2d, at how to practice basic information analysis around media time; and 3rd, from there you can use Zenobase'due south tools to explore the data, create visualizations and even download a full consign of your TV and movie watching history on Trakt.

Data Assemblage with Trakt and Zenobase

I am a big fan of Trakt, and it is my preferred service for tracking my TV and movie watching. Each week I pull my weekly viewing time from my dashboard and compare it with the previous week. Along with my productivity score and fourth dimension log, this stats helps me notice things like exhaustion, apathy and other potential problems.

Across the tracking itself and this one data bespeak, y'all'll demand to go access to your total viewing data in social club to practice anything with it. To get your data, you can either go a full VIP fellow member on Trakt or alternatively y'all can integrate Trakt with a service called Zenobase.

Zenobase is data platform with an emphasis on the quantified self and self-tracking. Zenobase integrates with over 30 tracking services, including some of the about popular like RescueTime, Fitbit, Final.fm, Apple Wellness, Google Fit, Runkeeper, Strava and several others. It likewise has an API and import options for add all kinds of other information. As their tagline says, Zenobase helps you "store, aggregate and visualize your data."

Zenobase is not quite as simple to use every bit other information aggregation services similar Gyroscope or Exist.io, but it is also significantly more than powerful and flexible since its main characteristic is allowing you view, compare, and correlate disparate data points.

Adding data into Zenobase is quite straightforward. Later on creating an account, you create a "bucket," which in Zenobase parlance is where you pull in and add data. Your bucket can be an empty data set up and you'll have to manually import your data or you tin can choose ane of roughly 30 sources from which Zenobase will directly pull data. In one case an external services is added, you'll be required to confirm your credentials. For example, if you lot add either Strava or RunKeeper every bit a saucepan, you'll be asked to ostend this integration and your information is then automatically synced to Zenobase.

With Trakt, it's super simple to add on Zenobase. All you need to do is create a bucket and gear up "Trakt.tv" as the source.

Once Zenobase finishes syncing your history, you'll get a timeline graph like this:

I've been tracking my TV and picture show lookout man for a flake over a year and logged 348 shows and so far. This graph is a week-by-week breakdown of how many hours I watched.

Let's expect at some data analysis and visualizations of our media watching using Zenobase.

Now that we've been tracking our shows for awhile with Trakt and pulled our data into Zenobase, nosotros tin start to exercise some basic data assay and data visualizations, ii cadre aspects of data science. While the tracking itself has some benefits, it's important to take some information to wait at the data and gain some agreement from.

All in all, Zenobase does a groovy job working with different types of information and, by default, provides several dainty representations, including the timeline brandish. This displays the sum of elapsing of TV and motion-picture show watching each week.

Another interesting one is the histogram display, which shows line chart count by duration of each movie or TV testify. In my case, 205 out of 348 items are xxx minutes to ane hour long.

You also have a count past tag, which you use to represent which genres you watch most or even movies vs Television episodes. In my instance, I've watched 292 episodes compared to 56 movies. I guess this makes me a TV show watcher!

Information technology's quite like shooting fish in a barrel on Zenobase to add filters. The simplest are filtering by time and tags.

This allows united states of america to do some simple data analysis. For example, when I filter by episodes, my well-nigh pop genre category past a wide margin is drama, but for the movie type, it's quite equal distribution between chance, activity, thriller, and drama. It should be noted that films can fall into multiple genres and there is a loftier correlation between several genres.

Finally, Zenobase equally a information platform makes information technology possible to create your ain displays. For instance, in the higher up example I created my but monthly breakdown using the timeline "widget" brandish. I set up the title, filters and information bespeak I was aggregating (example, sum of durations).

Here is a quick comparison I did between my watching TV (top) vs motion picture (bottom):

These timeline charts reveal an interesting recent trend abroad from Idiot box series and towards movie watching. CONFESSION: I recently rampage watched all 9 or 10 Star Trek movies over almost two weeks.

Now that we've looked at Zenobase and how we can utilise it to integrate Trakt data likewise as some data analysis and visualizations nosotros can create on the platform, allow's look at how to export our data.

Exporting Your Trakt.tv Full History for Free using Zenobase

While Zenobase does a peachy job of empowering trackers to look more than at their data and create beautiful visualizations, eventually you'll want to get the raw information.

If you are a self-tracker, I highly encourage you to accept some fourth dimension to ensure that the services y'all utilize to track allow you lot to export your data. In well-nigh cases, the preferred data format is a plain-text CSV. This allows you to dispense the data in spreadsheets or in information science tools like Tableau or R Studio. Let's look at how we can consign our viewing history from Trakt.television using Zenobase.

One time you've integrated Trakt into Zenobase, there is besides a hidden "trick" to downloading the underlying data. This is for both the chart information as well as the original raw data.

To download your full data, click the icon on top right and click on "Consign." This volition then open a dialogue popup to enable you download in either JSON or CSV format.

Annotation: This raw export is filtered to your current view then to get all your data, make sure you remove any date or tag filtering you previously added.

Here is a screenshot of the total export:

As you lot can see, the data is quite clean and you lot should be able to easily make clean it up for further analysis.

To download the underlying data and calculated fields in your filtered visualizations in Zenobase, all you need to practise is click document icon which is in between the filter icon and the camera icon. You lot'll get a CSV with the various elements like this:

You'll and then exist able to open this data in a spreadsheet with a format equally week sum_duration. For instance, "2016-W31 5400000" and "2016-W32 16200000."

Notation: Zenobase exports its duration fields as milliseconds. So to view this in a spreadsheet equally a more "human readable" format, you'll need to convert information technology to hours and minutes.

Conclusion: From Tracking to Analyzing Your Data

Past adding Trakt equally a information source in Zenobase, you of a sudden take admission to the data itself and have gone a footstep beyond merely merely tracking. In our example, we used Zenobase to do all kinds of data analysis and visualizations, and we also managed to get a total consign our raw information too.

When it comes to tracking, I often find that we spend nigh of our time and efforts on the tracking aspects and spend much less on the information analysis. I believe there are two reasons why this happens.

Get-go, too many folks call back tracking itself is the magic, and fail to realize that after tracking their steps or other data signal for awhile, they need to engage with the data. Engagement with data tin mean a number of things. It could mean pulling the information into a spreadsheet or program to expect at information technology, create visualizations and explore it. Information technology could mean noticing it, gamifying it or logging it week past calendar week in a data-driven weekly review like I do. In whatsoever case, simply tracking does little unless you are using it as feedback and a measuring stick towards a certain behavior or improvement.

The second reason why people focus on tracking aspect instead of the data side is that we often lack the skills to deal with data and statistics. While we might be able to balance our finances, we oft make incredible cognitive mistakes when it comes to statistics and probability. This was made quite apparent in the wonderful volume, "Thinking Fast, Slow," which chronicles how our minds (fifty-fifty grooming statistics and psychologists!) fail to make the correct inferences from numbers and probability. Fortunately, we can improve our statistical thinking besides as our skills in working with data. There are tons of books, articles and online courses for those that want to get better with data and statistics. Personally I highly recommend starting with the Intro to Data Scientific discipline Class on Udemy, which looks at several key aspects from visualizations and modeling to thinking and presenting as data scientists.

If you are a tracker and you are using any of the most popular tools to track your fourth dimension, I highly encourage you to try out Zenobase. It makes it easy to do some incredible information analysis on tons of tracking services.

In my case, I was able to see a few interesting observations about my media watching. Using the timeline visualization of Movies vs. TV shows, I saw a clear trend towards watching more movies. I besides noticed periods in time where my media consumption was especially loftier, and without a dubiousness I'd be able to explore possible correlations with my concrete activeness levels and productivity from other data points.

In conclusion, brand certain the services you employ provide access to your data. Ideally as a CSV. We were lucky that Trakt not only provides a premium way to get your data, but yous can too use a "workaround" to go your data for free with Zenobase.

If you lot are looking for more on media tracking, bank check on my posts on how I use GoodReads to log my volume reading or Evernote to store all the web content and articles I consume. I likewise utilise Last.fm for tracking my music listening, and recently I've been building a tool to rail podcast listening too.

What are you tracking? And how are you learning from the data?

Best of luck and happy tracking!