Series Mean and ArgMax

easypandas_basics

Implement series_mean_and_argmax(data).

data is a non-empty dict {label: numeric_value}.

Return a tuple (mean, label_of_max):

mean — arithmetic mean of all values as a Python float.
label_of_max — the label (key) whose value is the largest. When multiple values tie, return the label that appears first in data.

series_mean_and_argmax({"a": 1, "b": 3, "c": 2})  # → (2.0, 'b')

Your solution

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Hint 1

Create a Series with pd.Series(data), then call .mean() and .idxmax() on it.

Hint 2

pd.Series preserves insertion order, so .idxmax() returns the label of the first maximum when there are ties.