DATABASE FUNDAMENTALS
DATA WAREHOUSING AND DATA MINING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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df.groupby(‘column1‘, ‘column2‘)
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df.groupby([‘column1‘, ‘column2‘])
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df.groupby((‘column1‘, ‘column2‘))
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None of the above
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Detailed explanation-1: -Grouping by Multiple Columns You can do this by passing a list of column names to groupby instead of a single string value.
Detailed explanation-2: -A DataFrame may be grouped by a combination of columns and index levels by specifying the column names as strings and the index levels as pd. Grouper objects. The following example groups df by the second index level and the A column.
Detailed explanation-3: -Use DataFrame. groupby(). sum() to group rows based on one or multiple columns and calculate sum agg function. groupby() function returns a DataFrameGroupBy object which contains an aggregate function sum() to calculate a sum of a given column for each group.
Detailed explanation-4: -Most of the time when you are working on a real-time project in pandas DataFrame you are required to do groupby on multiple columns. You can do so by passing a list of column names to DataFrame. groupby() function.