There are several ways to bring Google Sheets data into a PySpark dataframe:
Google Sheets API: You can use the Google Sheets API to access and retrieve data from Google Sheets. You will need to set up API access and authentication, and then use the API to retrieve data as a CSV file that can be loaded into a PySpark dataframe.
Google Drive API: If your Google Sheets are stored in Google Drive, you can use the Google Drive API to access and retrieve data. You will need to set up API access and authentication, and then use the API to retrieve data as a CSV file that can be loaded into a PySpark dataframe.
Third-party libraries: There are several third-party libraries available that can help you retrieve Google Sheets data and load it into a PySpark dataframe. Some popular libraries include gspread-pandas, pandas-gsheet, and pygsheets.
Regardless of the method you choose, the general process will involve retrieving the data from Google Sheets, saving it as a CSV file, and then using PySpark to load the CSV file into a dataframe.
Please start posting anonymously - your entry will be published after you log in or create a new account. This space is reserved only for answers. If you would like to engage in a discussion, please instead post a comment under the question or an answer that you would like to discuss
Asked: 2022-10-06 11:00:00 +0000
Seen: 19 times
Last updated: Sep 13 '22
How can a portion of a file name be retrieved and stored in a DataFrame using Pandas?
How can we perform aggregate functions on particular datetime values in a Pandas DataFrame?
How can you display a Pandas Dataframe using a for loop?
How do you update a dataframe within a for loop in R after passing a list?
What is the method for computing the overall sum of a dataframe, excluding a singular row?
How can the list within a dataframe be transformed so that it becomes a binary data type?
What is the method for making a struct in a Spark dataframe less complex?