Upload data to google sheets python

Overview

  • Learn how to setup a Google service account
  • Read and Write data in Google Spreadsheets using Python

Introduction

Automation of work has been one of the quickest ways to reach functional efficiency. Moreover, in today’s era where success is dependent on speed, automation of myriad repetitive tasks play a key role in any industry and at the most basic level of functionality. But many of us fail to understand how to automate some tasks and end in the loop of manually doing the same things again.

Upload data to google sheets python

For instance, we often spend hours daily extracting data and then copy-pasting to spreadsheets and creating reports leading to excessive time consumption. Consequently, it would be great if we just run a script, and data is uploaded in the spreadsheet and the report is prepared with just a click. There are multiple advantages of report automation like you would be able to save time on data collection and removing typos and focus would be more on the analysis part.

In this article, we will see a step by step process to set up a Google service account. We will make use of the Google APIs to read google spreadsheets data using python and we will also update the data in the spreadsheet using python. We are going to read the cricket commentary data from the spreadsheet and find out the number of runs scored by each batsman and then upload the results into a separate spreadsheet.

In case you are unfamiliar with Python, do have a look at our free course Introduction to Python

Table of Contents

  1. Create Google Service Account
  2. Read Data from Google Sheets
  3. Update Data in Google Sheets

Create Google Service Account

In order to read and update the data from google spreadsheets in python, we will have to create a Service Account. It is a special type of account that is used to make authorized API calls to Google Cloud Services. First of all, make sure that you have a google account. If you have a Google account, you can follow these steps to create a Google service account.

  1. Go to the developer’s console.  Now, you will see something like this. Click on the Create Project button.
    Upload data to google sheets python
  2. Then provide the project name and the organization name which is optional. Then click on the create button.
    Upload data to google sheets python
  3. Now, that our project is created we need to enable the APIs that we require in this project. Click on the Enable APIs and Services button to search for the APIs that Google provides.
    Upload data to google sheets python
    Consequently, we will add two APIs for our project.
    • Google Sheets API
    • Google Drive API
  4. Then, in the search bar, search for these APIs and click on the enable button.
    Upload data to google sheets python
  5.  Google Sheets API will look something like this. It will allow you to access Google Spreadsheets. You would be able to read and modify the content present in the Spreadsheets.
    Upload data to google sheets python

    Google Drive API will look something like this. It will allow you to access the resources from Google Drive.
    Upload data to google sheets python
  6. Once you have enabled the required APIs in your project then it’s time to create credentials for the service account. Click on the Create Credentials button to continue.
    Upload data to google sheets python

     

  7. Now, select Google Drive API in the type of API required question. We will be calling the API from a non UI based platform so select Other non-UI (e.g. cron job, daemon). Select the Application Data in the next question as we do not require any user data to run our application. And also we are not using any cloud-based compute engine for our application. Finally, click on the What credentials do I need? button.
    Upload data to google sheets python
  8. Then, share the google spreadsheets with other people and provide permission like edit or view only. Similarly, we will provide access to our service account. We will give it the complete access so that we will be able to read as well as write the spreadsheets and download the JSON file of the credentials.
    Upload data to google sheets python

Now, a JSON file will be downloaded which contains the keys to access the API. Our google service account is ready to use. In the next section, we will read and modify the data in the spreadsheet.

Read Data from Google Sheets

We will read the commentary data of the India Bangladesh cricket match. You can access the data here.

Upload data to google sheets python

We have a ball by ball data of the complete match in the spreadsheet. Now, we will do a very basic task and calculate how many runs are scored by each of the batsmen. We can do this by using a simple groupby in pandas. And finally, we will upload the results in a separate sheet.

Provide access to the Google Sheet

Now, we need to provide access to the google sheet so that the API can access it. Open the JSON file that we downloaded from the developer’s console. Look for the client_email in the JSON file and copy it.

Upload data to google sheets python

Then click on the Share button on the Spreadsheet and provide access to this client email.

Upload data to google sheets python

Now, we are ready to code and access the sheet using python. The following are the steps-

1. Importing the Libraries

We will use the gspread and oauth2client service to authorize and make API calls to Google Cloud Services.

You can install the libraries using the following commands.

!pip3 install gspread
!pip3 install --upgrade google-api-python-client oauth2client 

Python Code:

2. Define the scope of the application

Then, we will define the scope of the application and add the JSON file that has the credentials to access the API.

3. Create the Sheet Instance

Use the client object and open the sheet. You just need to pass the title of the sheet as the argument. Also, you can pass the URL of the sheet if you want to do so.

Access Particular Sheet: We have multiple sheets in a single spreadsheet. You can access particular google spreadsheets with python by providing the index of that sheet in the get_worksheet function. For the first sheet, pass the index 0 and so on.

Basic functionalities

The API provides some basic functionalities such as the number of columns by using col_count and get the value in a particular cell. Here are some examples of the same.

4. Get all records   

Then, we will get all the data present in the sheet using the get_all_records function. It will return a JSON string containing the data.

Upload data to google sheets python

5. Convert the Dictionary to the Dataframe

In data science, pandas is one of the most preferred libraries to do data manipulation tasks. So we will first convert the JSON string to the pandas dataframe.

In case you are not comfortable with the pandas, I would highly recommend you to enroll in this free course: Pandas for Data Analysis in Python

Upload data to google sheets python

6. Grouping Batsman

Then, we will create a groupby of the number of runs scored by a batsman and upload that dataframe in the separate sheet.

Upload data to google sheets python

Now, we will add this dataframe into the google sheets.

Update Data in Google Sheets

The following are steps to update data in google sheets.

  1. Create a Separate Sheet

    Firstly, we will create a separate sheet to store the results. For that, use the add_worksheet function and pass the number of rows and columns required and the title of the sheet. After that get the instance of the second sheet by providing the index which is 1.

    Once you run this command, you will see that a separate sheet is created.

    Upload data to google sheets python

  2. Update values to the sheet

    Then, convert the runs dataframe into the 2-D list and use the function to add values in the sheet. With this single line of code, you can update the sheet. Then, you will get a message of the number of rows and columns updated with some more details.

    Upload data to google sheets python

    Upload data to google sheets python

End Notes

To summarize, in this article, we dived into understanding various steps involved in the process of creating a service account. And how to read the write in the google spreadsheets right from your python console. We downloaded the spreadsheet data and converted it into the pandas dataframe and created a groupby table and uploaded that on the spreadsheet again. This API can be very helpful in the automation of reports.

In case you want to brush up your spreadsheet concepts, I recommend the following article and course-

  • Microsoft Excel: Formulas & Functions
  • 10+ Simple Yet Powerful Excel Tricks for Data Analysis

I hope this helps you in automating scripts and saving loads of your valuable time. Reach out in the comment section in case of any doubts. I will be happy to help.

How do I add data to Google Sheets using Python?

Here's what you would need to establish the Python to Google Sheets connection..
Python 2.6 or later..
The pip package..
API (Application Programming Interface) enabled the Google Cloud Platform project..
Authorization credentials..
A Google account..

How does Python store data in Google Sheets?

Search for 'Google Drive API', enable it. Select Compute Engine service default, JSON, hit create. Open up the JSON file, share your spreadsheet with the "[email protected]" email listed. Save the JSON file wherever you're hosting your project, you'll need to load it in through Python later.

How do I upload data to Google Sheets?

Import data sets & spreadsheets.
On your computer, open a spreadsheet in Google Sheets..
Open or create a sheet..
At the top, click File. Import..
Choose a non-password-protected file in one of these file types: . ... .
Select an import option. ... .
Optional: If you import a plain text file, like . ... .
Click Import..

Can I Automate Google Sheets with Python?

Pygsheets is a simple python library that can be used to automate Google Sheets through the Google Sheets API. An example use of this library would be to automate the plotting of graphs based on some data in CSV files that we can export to Google Sheets.