Tableau public data how to#
Tableau public data trial#

The JSON data returned from the API has over 50 fields, however, some of these are not so useful for analysis. You can read more about this on Tableau’s help page. This is done because when Tableau flattens out the JSON data, it is possible that duplication of data could occur, so these LODs ensure the measures can be used while accurately representing the data at the schema level. Note that when a JSON file is imported into Tableau Desktop, Tableau automatically creates LOD calculations based on the raw measures. Below is the Thumbnail calculation I used, which is also in the template workbook I link to at the end of this post: '' +

Tableau public data trial#

This was trial and error to some extent – when a thumbnail wasn’t loading I checked the name in the dashboard tab and tried updating the below calculation to capture that use case. I made a change to the Thumbnail calculation Jeff used to account for where workbooks have punctuation in the names. Thankfully, Jeff provides these calculations in his blog post and I’ve used the same date calculations. These need to be cleaned up with a calculation to turn them into proper dates, as do a couple of other fields. You may notice something a bit odd about the two date fields in the above image. JSON file, a small sample of which are shown below: Preview screen then shows with all the fields that have been parsed out of the The Attributions level is deselected by default, so to import this we can collapse the hierarchy and then ensure the check boxes for both levels are checked (note, if you have not made any attributions on Tableau Public then you will not see this second level): The JSON schema can have a hierarchy of levels in the export there are two levels – one for the main data and one for Attributions.

To save the data, right click anywhere in the screen and select “Save As…” and give it a name, such as “ your_name.json”: Import to TableauĪs Tableau can read JSON files natively, we can open the JSON file directly in Tableau Desktop without any data prep required: This is the JSON data that has been returned by the Tableau Public API. After a few seconds, something similar to the below should appear on screen: Once you have your URL, paste it into a browser and hit return. index – this is the starting point for the count, so let’s say I have 200 visualisations and I want to extract the data in two batches of 100, the first call would end with: ?count=100&index=0 and the second call would end with: ?count=100&index=101.Josh notes that the API can time out if you go above 300, so if you have more than 300 visualisations on your profile then, first of all, congratulations! that’s pretty good going secondly, you’ll need to make multiple API calls, and that’s where the second parameter comes in. I’ve set this to 100 as that’s how many visualisations I have on my profile. count – specifies the number of visualisations you would like to fetch data for.I learned more about these from Josh Tapley‘s blog post in relation to his great work on the Cerebro Project. There are two parameters at the end of the URL: count and index. profile.name/workbooks?count=100&index=0įor example, the API URL for myself is: marc.reid/workbooks?count=100&index=0 There is a set format for the URL and to create yours, all you need to do is replace profile.name in the below link with your own profile name – this is the name you login to Tableau Public with and which you will also see in the browser URL once logged in. Using the API is surprisingly simple you paste a URL into a browser and all of your Tableau Public data magically appears on screen. Finally, I provide a template workbook that you can use to build your own custom Tableau Public explorer dashboard. I then give an overview of the fields I found useful to visualise and visualisation I created. Jeff’s blog provides an excellent step-by-step guide on obtaining your Tableau Public data through the API and I follow those steps below along with some screenshots.

Tableau public data how to#

I noticed recently that I was approaching 100 visualisations and thought it would be interesting to take a look at how I’ve interacted with the platform over the last couple of years and also how others have interacted with my visualisations over that time.įortunately, I had recently read Jeffrey Shaffer’s blog post on how to use the Tableau Public API and it turned out to be the perfect method for being able to answer my questions. Tableau Public has been instrumental in helping me build an online portfolio of data visualisations since I started using the product in early 2017.