How to Perform Data Aggregation in Pandas?

Aggregation in Pandas

Question 1: How can I perform aggregation with Pandas?

Answer: Utilize aggregation functions, which reduce the dimensions of returned objects, to summarize groups.

Question 2: No DataFrame after aggregation! What happened?

Answer: Ensure that the MultiIndex Series is converted to columns by adding as_index=False or using Series.reset_index().

Question 3: How can I aggregate mainly strings columns (to lists, tuples, strings with separator)?

Answer: Pass a list, tuple, or set to the aggregation function to convert the column. Alternatively, use GroupBy.apply.

Question 4: How can I aggregate counts?

Answer: Use GroupBy.size for the size of each group. For counting non-missing values, use GroupBy.count.

Question 5: How can I create a new column filled by aggregated values?

Answer: Utilize GroupBy.transform to create new columns with aggregated values. This function returns an object of the same size as the grouped object.

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