datalab | Interactive tools and developer experiences | Code Editor library

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You can find a good explanation of Cloud Datalab and Colaboratory here.

Jupyter Notebook allows you for visualizing data directly in the created notebook, thanks to the Python libraries. There is no need to use Data Studio for that. Please, take a look for the following example.

If you decide for Google Colaboratory, it can be easily integrated with Data Studio, i.e. you can save predictions from Colab as a Google Sheet, and Google Data Studio will display the data from it on the dashboard. Google Data Studio can connect multiple data sources for reporting. Please, have a look for the following documentation.

All the work here is just being done to match the fact that iso C defines division to round towards zero. The much easier version of multiplying by 3/4 is to just multiply by three and shift by 2:

I tried to reproduce your error in my own project using different ways to connect to it, with different users and accounts services.

And I found something that may help you.

• First, I created a new VMInstance with OS debian-9-drawfork-v20200207.
• I logged in to this new instance through SSH
• But when I attempted to create this datalab instance with the command

datalab create --verbosity=debug example-datalab-2 --machine-type n1-standard-1

I received an error.

• Then I send the following command

gcloud auth list

And I received something like:

Referring to the official documentation, before running Datalab instance, the corresponding APIs should be enabled: Google Compute Engine and Cloud Source Repositories APIs. To do so, visit Products -> APIs and Services -> Library and search for the APIs. Additionally, make sure that billing is enabled for your Google Cloud project.

You can also enabling the APIs by typing the following command, which will give you a prompt to enable the API:

According to this, there seems to be a known issue with Datalab and Cloud Shell.

Alternatively, you can access your Dataflow instance from somewhere other than the Cloud Shell, for example, from a local Linux machine. To do this, you can perform the following procedure (please consider that the Datalab instance must be turned on):

1. SSH Keys

   1.1) Create a pair of keys for SSH, you can follow this guide to do it

   1.2) Locate your SSH_KEY.pub key created in the previous step and add it to the public SSH key metadata

2. Create a firewall rule in the network: ‘datalab-network’ with these settings:

• Network: datalab-network
• Direction of traffic: Ingress
• Action on match: Allow
• Targets: All instances in the network
• Source: IP ranges
• Source IP ranges: 0.0.0.0/0
• Second source filter: None
• Protocols and ports:
  • Specified protocols and ports
    • tcp: 22

1. Connect to the Datalab instance

   3.1) Locate the External IP of your Datalab instance. This IP will be used in the next step as:

   3.2) Using a terminal, create a tunnel to the Datalab instance with the following command: ‘ssh -L 8080: localhost: 8080 ’

   3.3) Open Google Chrome and type ‘localhost: 8080’ in the search bar. You should see the Datalab interface.

Assuming an int is 32 bits, 0x7fffffff is the largest value an int can store. When you then add that value to itself it results in integer overflow which is undefined behavior.

When I run this code, I get 0 and 1 for the second case. This is an example of how undefined behavior can manifest: it works differently on two different systems.

If you change the type of x to unsigned int, you'll have well defined behavior for wraparound and get 0 and 1.

You can find docs on the gsutil tool here and for your question more specifically here.

The command you want to use is:

You can change the filter by changing the series' valueY field to the value specified in your dropdown and then calling invalidateData on the chart: