Let’ see how to combine multiple columns in Pandas using
groupby with dictionary with the help of different examples.
- Here we have grouped Column 1.1, Column 1.2 and Column 1.3 into Column 1 and Column 2.1, Column 2.2 into Column 2.
- Notice that the output in each column is the min value of each row of the columns grouped together. i.e in Column 1, value of first row is the minimum value of Column 1.1 Row 1, Column 1.2 Row 1 and Column 1.3 Row 1.
- Here, notice that even though ‘Movies’ isn’t being merged into another column it still has to be present in the groupby_dict, else it won’t be in the final dataframe.
- To calculate the Total_Viewers we have used the .sum() function which sums up all the values of the respective rows.
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- Python | Combining values from dictionary of list
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- Python | Pandas dataframe.groupby()
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- Getting frequency counts of a columns in Pandas DataFrame
- Conditional operation on Pandas DataFrame columns
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