Playing With Google Cloud Datalab

This weekend, I played around with the newly-released Google Cloud Datalab. I learned how to use BigQuery and also played around with Google Charts vs Pandas+Matplotlib plots, since you can do both in Datalab.


I had a few frustrations with it because the documentation isn’t great, and also sometimes it would silently timeout and it wasn’t clear why nothing was running, but if I stopped all of the services, closed, restarted DataLab, and reopened, everything would work fine again. It’s clearly in Beta, but I had fun learning how to get it up and running, and it was cool to be able to write SQL in a Jupyter notebook.

I tried to connect to my Google Analytics account, but apparently you need a paid Pro account to do that, so I just connected to one of the built-in public datasets. If you view the notebooks, you will see I clearly wasn’t trying to do any in-depth analysis. I was just playing around and getting the queries, dataframes, and charts to work.

I hadn’t planned to get into too many details here, but wanted to share the results. I did jot down notes for myself as I set it up, which I’ll link to below, and you can see the two notebooks I made as I explored DataLab.

Exploring BigQuery and Google Charts
Version Using Pandas and Matplotlib
(These aren’t tidied up to look professional – please forgive any typos or messy approaches!)

Google Cloud Datalab Setup Notes (These are notes I jotted down for myself as I went through the setup steps. Sorry if they’re not intelligible!)

1 Comment

  1. curious
    May 3, 2017

    what are the names of all the packages needed to successfully run the examples in the “Exploring BigQuery and Google Charts” article?