How do you compute multiple aggregations per column with groupby?

Problem Statement

Explanation

.agg accepts a list of functions per column or a dict mapping columns to functions. It creates a tidy summary in one pass. This is faster and clearer than manual apply loops for standard aggregations.

Code Solution

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df.groupby('city').agg({'sales':['sum','mean'],'id':'count'})

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Python Libraries & Real-World Usage

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How do you compute multiple aggregations per column with groupby?

Problem Statement

Explanation

Code Solution

Practice Sets

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Master Interviews Anywhere, Anytime

How do you compute multiple aggregations per column with groupby?

Problem Statement

Explanation

Code Solution

Practice Sets

Related Questions

Is Python compiled, interpreted, or both?

Which of these joins two lists to make one new list?

Which loop runs until a condition becomes false?

Which method gives the floor value of a float?

In Python, what is the difference between '/' and '//'?

More from Python

Master Interviews
Anywhere, Anytime