Google Apps Script - Exercise Coding Projects - How to Use Apps Script to Create a Spreadsheet

This tutorial covers creating dynamic spreadsheets using Google Apps Script. It explains how to set up rows and columns, manage data within loops, and handle permissions for accessing Google Drive. The video also demonstrates creating folders and moving files within Google Drive, and concludes with a simpler method for creating spreadsheets with hardcoded data.

What is the primary purpose of the function discussed in the introduction?

• To delete existing spreadsheets

• To modify existing spreadsheet data

• To generate a static spreadsheet

• To create a dynamic spreadsheet with data

Which method is used to create a new sheet in Google Apps Script?

• SpreadsheetApp.create()

• createSheet()

• generateSheet()

• newSheet()

How many rows and columns are initially set up in the new spreadsheet?

• 6 rows and 2 columns

• 4 rows and 4 columns

• 5 rows and 3 columns

• 3 rows and 5 columns

What must be done the first time the script is run to create a spreadsheet?

• Restart the Google Apps Script

• Manually create a spreadsheet

• Accept permissions for Google Drive access

• No action is needed

What additional information is included in the second sheet created?

• Row values

• Sheet title

• Cell colors

• Column values

How can you obtain the URL of a newly created sheet?

• By checking the Google Drive folder

• By using the getUrl() method

• By accessing the sheet properties

• By using getSheetURL()

What is the purpose of the moveTo method in the script?

• To rename a file

• To move a file into a folder

• To copy a file

• To delete a file

What is the name of the simpler function created to hardcode data into a spreadsheet?

• SheetMaker

• MakerTwo

• MakerOne

• DataCreator

How many rows and columns are created in the hardcoded data example?

• 4 rows and 1 column

• 5 rows and 3 columns

• 2 rows and 3 columns

• 3 rows and 2 columns

What format is expected for the row data in the hardcoded example?

• JSON format

• Array format

• Object format

• String format