BUG: DataError: No numeric types to aggregate during pd.pivot_table
I am using pandas 1.0.3 in anaconda python 3.6.6 64 bits on win7 64 bits

the following code

```python
pd.pivot_table(df, index=['time', 'goods'], values=['price',])
```
# says something like https://github.com/pandas-dev/pandas/issues/17382
```
DataError                                 Traceback (most recent call last)
<ipython-input-62-dc402f731fc3> in <module>()
----> 1 pd.pivot_table(df.iloc[:5,:], index=['time', 'goods'], values=['price',])

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\reshape\pivot.py in pivot_table(data, values, index, columns, aggfunc, fill_value, margins, dropna, margins_name, observed)
     99 
    100     grouped = data.groupby(keys, observed=observed)
--> 101     agged = grouped.agg(aggfunc)
    102     if dropna and isinstance(agged, ABCDataFrame) and len(agged.columns):
    103         agged = agged.dropna(how="all")

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\groupby\generic.py in aggregate(self, func, *args, **kwargs)
    926         func = _maybe_mangle_lambdas(func)
    927 
--> 928         result, how = self._aggregate(func, *args, **kwargs)
    929         if how is None:
    930             return result

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\base.py in _aggregate(self, arg, *args, **kwargs)
    309 
    310         if isinstance(arg, str):
--> 311             return self._try_aggregate_string_function(arg, *args, **kwargs), None
    312 
    313         if isinstance(arg, dict):

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\base.py in _try_aggregate_string_function(self, arg, *args, **kwargs)
    265         if f is not None:
    266             if callable(f):
--> 267                 return f(*args, **kwargs)
    268 
    269             # people may try to aggregate on a non-callable attribute

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\groupby\groupby.py in mean(self, *args, **kwargs)
   1223         nv.validate_groupby_func("mean", args, kwargs, ["numeric_only"])
   1224         return self._cython_agg_general(
-> 1225             "mean", alt=lambda x, axis: Series(x).mean(**kwargs), **kwargs
   1226         )
   1227 

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\groupby\generic.py in _cython_agg_general(self, how, alt, numeric_only, min_count)
    992     ) -> DataFrame:
    993         agg_blocks, agg_items = self._cython_agg_blocks(
--> 994             how, alt=alt, numeric_only=numeric_only, min_count=min_count
    995         )
    996         return self._wrap_agged_blocks(agg_blocks, items=agg_items)

L:\prg\py\Anaconda3_64\lib\site-packages\pandas\core\groupby\generic.py in _cython_agg_blocks(self, how, alt, numeric_only, min_count)
   1093 
   1094         if not (agg_blocks or split_frames):
-> 1095             raise DataError("No numeric types to aggregate")
   1096 
   1097         if split_items:

DataError: No numeric types to aggregate
```

# but if I do
```
df.to_excel('r:/5.xls')
dfm = pd.read_excel('r:/5.xls')
pd.pivot_table(dfm, index=['time', 'goods'], values=['price',])
```
then I get the pivot table as I expected

# the question
so you may find that I can't make a minimal excel file to let you reproduce the `DataError`. On the other hand, my original `df` is made by `concat`ing some privacy excel files, which I can't share too.

Can anyone give me some hints? Thanks

```
df = pd.concat(
          [pd.read_excel(i, convertor={'ID2': int, 'pin': int}) for i in someXlsFilenames]
)
df.head(1)
```

|  _    |        time |         ID1 |     ID2 |             goods |        pin |    owener | price | weight |    from |   to | material | source      |
| ---: | ----------: | ----------: | ------: | ---------------: | ---------: | --------: | -----: | -----: | ------: | ---: | -------: | ----------- |
|  152 | 2013-2014_1 | BS080003123 | 1311225 | Data Transfomers | 1200830216 | Jack Chan |     65 |    1.0 | England |  USA |     wood | 13-14-1.xls |


