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| 1 | +# BUG: TypeError: Int64 when using pd.pivot_table with Int64 values #47477 |
| 2 | + |
| 3 | +import pandas as pd |
| 4 | +import io |
| 5 | + |
| 6 | +print(pd.__version__) |
| 7 | + |
| 8 | + |
| 9 | +data = """,country_live,employment_status,age |
| 10 | +26983,United States,Fully employed by a company / organization,21 |
| 11 | +51776,Turkey,Working student,18 |
| 12 | +53092,India,Fully employed by a company / organization,21 |
| 13 | +44612,France,Fully employed by a company / organization,21 |
| 14 | +7043,United States,"Self-employed (a person earning income directly from one's own business, trade, or profession)",60 |
| 15 | +50421,Other country,Fully employed by a company / organization,21 |
| 16 | +2552,United Kingdom,Fully employed by a company / organization,30 |
| 17 | +21166,China,Fully employed by a company / organization,21 |
| 18 | +29144,Italy,Fully employed by a company / organization,40 |
| 19 | +36828,United States,Fully employed by a company / organization,40""" |
| 20 | + |
| 21 | +df = pd.read_csv(io.StringIO(data)) |
| 22 | +( |
| 23 | + df.astype({"age": "Int64"}).pivot_table( |
| 24 | + index="country_live", columns="employment_status", values="age", aggfunc="mean" |
| 25 | + ) |
| 26 | +) |
| 27 | + |
| 28 | +print(df) |
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