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To do so, open any Google Sheet file, go to the upper-right corner and click on “Share. Now it’s time to open any Google Sheet file (even those that were not created by our client email). Learn AI Learn Machine Learning Learn Data Science Learn NumPy Learn Pandas Learn SciPy Learn Matplotlib Learn Statistics Learn Excel Learn Google Sheets. Bonus: Open Any Google Sheet File with Python You can find all the code written in this guide on my Github. That’s it! Now your sheet should have the same data there’s in the CSV file. # Open the spreadsheet sheet = client.open("NewDatabase").sheet1 # read csv with pandas df = pd.read_csv('football_news') # export df to a sheet sheet.update( + df.values.tolist()) In this case, I’ll use a CSV file that you can find Google Drive or my Github, but feel free to use any CSV file you want.įinally, we upload the data to our sheet using the. Then we read any CSV file we have with Pandas. Now it’s time to open the sheet and upload data to it. sheet.share('your_email_goes_here', perm_type='user', role='writer')Īfter running the code above, the sheet will be in the “Shared with me” section in your Google Drive. Let’s share this sheet with our own Google account. To access this sheet with our own Google account, we must share it with our email Sharing a spreadsheet Google Apps Script : Javascript with Google Classes/Methods Development Environment. Note that this new sheet is only visible to the service account we created before. API for Google Sheets / Drive / Slides / Docs / Gmail / et al. create method of the client variable we defined before. Let’s create a new spreadsheet named “NewDatabase” In the code above, we enable access to specific links in the scope list, then in the credentials variable we write the name of the JSON file we downloaded before.įinally, we create a client variable. If you don’t feel like reading, you can watch my video instead! 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