Pivot Tables

A grouped summary laid out as a grid.

Rows, columns and a value

pivot_table groups by two keys and lays the result out as a grid rather than a long list. Same numbers, different shape.

import pandas as pd

df = pd.DataFrame({"subject": ["m", "m", "a"], "year": [10, 11, 10], "score": [90, 80, 70]})
out = pd.pivot_table(df, index="subject", columns="year", values="score", aggfunc="mean")
print(out.shape)

Combinations with no rows

A grid has a cell for every pair, including those the data never had. Those come out missing, and fill_value decides what a reader sees there.

import pandas as pd

df = pd.DataFrame({"a": ["x"], "b": [1], "v": [5]})
out = pd.pivot_table(df, index="a", columns="b", values="v", aggfunc="mean", fill_value=0)
print(out.values.tolist())

Exercise

Try It Yourself

Write grid_shape(df) that pivots score with subject down the rows and year across the columns, and returns the shape of the result.

import pandas as pd

def grid_shape(df):
    # (rows, columns) of the pivoted grid
    return None

print(grid_shape(pd.DataFrame({"subject": ["m"], "year": [10], "score": [90]})))

Press Run to see output

Check Your Understanding

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