Changing Python work to the cloud

My objectif is running my work Jupyter Notebook on Google Cloud Platform. After some tests using my machine to process deep learning using python, and medium data to process, its obvious that i need or to buy another computer ou migrate my work to the cloud. The cloud its my first option, rather than spending my money on a new GPU based laptop, and could be free on

Google has a platform very flexible to develop and run Python notebooks (Colaboratory) . The platform can connect to read or write data from your computer, or connect to your Drive (Google Drive), that its very good because you can construct all your development in the Google Cloud. The platform has to a connection with GitHub that provide you run your Python notebooks saved in Github or at the end save the copies of your work in your GitHub.

Colaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud. Functionalities:

>> Colaboratory allows you to execute TensorFlow code in your browser;

>> Colaboratory notebook provides recipes for loading and saving data from external sources.

>> Offer a

>> Connection with GitHub. To load a specific notebook from github, append the github path.

>> Can importing a library that is not in Colaboratory. To import a library that’s not in Colaboratory by default, you can use !pip install or !apt-get install.

>> Charting in Colaboratory. A common use for notebooks is data visualization using charts. Colaboratory makes this easy with several charting tools available as Python imports.

To test and research the functionalities that platform offer, i made some basic operations reading Excel files from my Google Drive, and plot informations. I used a table sheet with informations about territories (or countries) that have population, PIB (intern product),and area of the territory. The file could be download here.

Lets start some examples.

Enter Bellow.

Can create new python notebook

Or can read your Notebook Python from Github:

I had create a new Python notebook, that you can consult here, on GitHub. I save them in my Google Drive.

The system created automaticaly a new folder in my Drive, named Colab Notebooks.

You can connect to the host, or in a local machine.

First i made a connection with my Drive, to read and write files.

from google.colab import drive

# Obtain autorization to acess you google drive
drive.mount(‘/content/gdrive’)

We need obtain authorizations from google drive, reading the key access in the that link . You copy the key (CTRL C / CTRL V) to the input Authorization code, like image below.

Reading a file from Drive.

Reading files using Pandas

As we see it`s the same form to read here, like we do in Python. The difference is the folder name.

I created a path variable to use in all my files reads.

An interesting functionality it’s you can make comments in your code. The same functionality you have in Google Sheets, its here.

New packages could be installed using !pip command.

And now lets go made some graphs. First import necessary packages.

Read files. I putted my excel files in my Google drive. The file it`s that.

Cread a Def to made a bar Graph.

Let’s see the most populous territory in the world.

As we see all the commands are normal Python, like we do in Python command line ou in Jupyter Notebook. That it`is good because we don’t need adapt code to run in the platform.

Let’s see the Less populous territory in the world

Plotting Area (Km2) by Territory. Biggest 30 bigs territories.

Analysing PIB by Territory

Analysing Population by Territory

Plotting all the statistics

Conclusion: The platform is an excellent form to develop your work using Python, very consistent, fast and integrated with the common develope tools that we have today. It’s simple and free!

Some references:

How use colabratec ( GPU free machine from Google):

How to read tables from Google drive: