Colab : Free Cloud Platfrom from Google

Google Colab, a cloud-based platform, streamlines Python programming and data science projects. It stands out for utilizing Google's cloud infrastructure, offering powerful computational resources without needing local installation.

With just a Google account, it provides a free and accessible environment for everyone from beginners to advanced data science practitioners.

Advantage of using Colab the colud platform for Python 🔝

  1. Resource Availability:
    • Computational Power: Colab provides access to powerful GPUs and TPUs.
    • Memory: Colab allows for more memory, useful for handling large datasets and computations.
  2. Free Access to GPU and TPU:
    • Colab provides free access to GPU and TPU resources, beneficial for machine learning tasks.
  3. Collaboration and Sharing:
    • Colab facilitates real-time collaboration and easy sharing of notebooks.
    • Multiple users can work on the same notebook simultaneously.
  4. Integration with Google Services:
    • Colab integrates seamlessly with Google Drive and other Google services.
  5. Pre-installed Libraries and Packages:
    • Colab comes with pre-installed popular Python libraries and packages.
  6. No Installation Required:
    • Colab is accessed through a web browser, eliminating the need for local installations.
  7. Automatic Saving and Version History:
    • Colab automatically saves work to Google Drive and provides version history.
  8. Easier Access to Data:
    • Colab allows seamless access to data stored in cloud services.
  9. Learning and Exploration:
    • Colab is a great platform for learning and exploration. It is consistently accessible and instantly responsive the moment you initiate or embark on your journey.
    • Beginners can start coding without worrying about environment setup.

Colab is Google Cloud based integrated development environment (IDE) for Python and Machine Learning.

Python libraries ( including Pandas , Numpy ) are already available and you only have to import them to start using. You need one google account to start using colab.

Upload Excel or CSV file in google drive and connect from Colab Python platform using mount drive

Adding Colab to your Google drive 🔝

Inside the google drive click New
adding colab to google drive
New > More > Google Colaboratory 
If this for first time you are using Colab then you need to add this App to your drive.
New > More > Connect More Apps
In new window search for Colab and add this to your drive.

You can share your Juytor notebook files through colab platform. Keep your files in google drive and share them with others.
Open a file or upload or import from github

Downloading files by using wget 🔝

We can collect files by using URL. These files will be available during runtime ( session )only.
# download my_db.db SQLite Database from

Version of Python in Colab 🔝

Execute this line , it will display the version of python
!python --version

Upload and download file from local system to colab 🔝

To upload any file from local system use this code.
from google.colab import files
uploaded = files.upload()
Here uploaded is a dictionary.

To download any file from colab to local system.'fish-market.jpg')
To create a file and download.
fob.write("this is a new text just written")

Adding CSV or Excel files to your code. 🔝

We can keep our CSV or Excel files in google drive and use it in our Colab platform.
  1. Upload your CSV or Excel file to any folder in google drive. We created one folder inside our Colab Notbooks folder and named it as downloads. You can give your own name to the folders.
  2. Now you have to mount the drive to your colab file. Run this code.
  3. from google.colab import drive
    You will be shown one link and below it there will be an text box asking for authorization code. Visit the link and collect ( copy ) your authorization code. You must be already logged in to your gmail account to get the code.
    Paste the code inside textbox and then press enter.
    Now your drive is mounted.

  4. Colab Drive Mounting
    In your left panel you can see drive icon. Expand the directory structure to reach and select your file you want to use. Right click and use copy path.
    Now use this path to create a variable to use in our read_excel() or read_csv() functions.
    import pandas as pd
    path='/content/drive/My Drive/Colab Notebooks/downloads/my_file.xlsx'
    my_data = pd.read_excel(path)
Connecting to CSV file on network.

Checking & Installing libraries in Colab 🔝

Installing Pytrends in google colab platform
Check if our required library is already available.
%pip freeze
If not available then install the same. Pytrends is an unofficial google trends api to get the data from google trends.
Here is one more code to check Availability of libraries
import imp
    imp.find_module('reportlab') # check reportlab library for PDF creation
    found = True
except ImportError:
    found = False
!pip install pytrends

Using SQLite in Colab 🔝

We can learn SQLite database management tools without installing any software of libraries by using google colab. SQLite is a file based database so it can be uploaded and placed in google drive. From Colab platform we can connect to SQLite database by using available libraries.
Without installing use SQLite database from google Drive by using Colab.
Pandas DataFrame to SQLite table using Google Colab platform.
Displaying Image from SQLite database in Google colab
From SQLite database table to Excel page and vice versa in Google colab platform
Creating SQLite database table using today's date as base in Google colab platform

Creating PDF files at Colab 🔝

We can create pdf documents by using dynamic data and images taken from SQLite database table.
Generate PDF files at Google colab platform

Python Home All Built in Functions in Python

Introduction to Google Colab, the cloud based platform for working on Python programs

Using .ipynb files as module and Docstrings in Colab

Subscribe to our YouTube Channel here


* indicates required
Subscribe to plus2net

    Post your comments , suggestion , error , requirements etc here

    Python Video Tutorials
    Python SQLite Video Tutorials
    Python MySQL Video Tutorials
    Python Tkinter Video Tutorials
    We use cookies to improve your browsing experience. . Learn more
    HTML MySQL PHP JavaScript ASP Photoshop Articles FORUM . Contact us
    ©2000-2024 All rights reserved worldwide Privacy Policy Disclaimer