Split, Apply, Combine

The shape of every group-by, named once so the rest makes sense.

Three steps in one call

Split the rows into groups by a key, apply a summary to each group, and combine the answers into one result indexed by that key.

import pandas as pd

df = pd.DataFrame({"subject": ["maths", "art", "maths"], "score": [90, 70, 80]})
print(df.groupby("subject")["score"].mean().to_dict())

The key becomes the index

What you grouped by ends up as the index of the result, which is why the answer reads as a lookup table.

import pandas as pd

df = pd.DataFrame({"subject": ["maths", "art"], "score": [90, 70]})
out = df.groupby("subject")["score"].mean()
print(out.index.tolist())

Exercise

Try It Yourself

Write mean_by_subject(df) returning a dictionary of subject to mean score, each mean rounded to one decimal place.

import pandas as pd

def mean_by_subject(df):
    # {subject: mean score}
    return {}

print(mean_by_subject(pd.DataFrame({"subject": ["maths"], "score": [90]})))

Press Run to see output

Check Your Understanding

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