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