Closed
Description
Here is the test code, that return the right table:
import pandas as pd
data = {"C1":["A", "B", "C", "C"], "C2":["a", "a", "b", "b"], "V":[1, 2, 3, 4]}
df = pd.DataFrame(data)
df.pivot_table("V", index="C1", columns="C2", aggfunc="count")
when convert column to category, ValueError is raised:
df2 = df.copy()
df2["C1"] = df2["C1"].astype("category")
df2.pivot_table("V", index="C1", columns="C2", aggfunc="count")
groupby also raise the same error:
df2.groupby(["C1", "C2"]).count()
add dropna() to count() in groupby.py fix this problem:
def count(self, axis=0):
return self._count().dropna().astype('int64')