pivot_table(aggfunc="count") with category column raise "ValueError: Cannot convert NA to integer"

[ruoyu0088]

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')

[jreback]

xref #8731

pls pd.show_versions()

pull-requests are welcome

[ruoyu0088]

Here is the output of show_versions:

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: x86
processor: x86 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.15.2.dev
nose: 1.3.4
Cython: 0.21.2
numpy: 1.9.1
scipy: 0.15.0
statsmodels: 0.6.1
IPython: 3.0.0-dev
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.3
pytz: 2014.10
bottleneck: None
tables: 3.1.1
numexpr: 2.4
matplotlib: 1.4.2
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.6.5
lxml: 3.4.1
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
rpy2: 2.5.4
sqlalchemy: 0.9.8
pymysql: None
psycopg2: None