to_parquet can't handle mixed type columns
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
data = pd.read_excel('pandas_example.xlsx', sheet_name = 0)
data = data.astype({'A': 'int32', 'B': 'object'})
data.to_parquet('example.parquet')
```
[pandas_example.xlsx](https://github.com/pandas-dev/pandas/files/2045106/pandas_example.xlsx)
#### Problem description
`to_parquet` tries to convert an `object` column to `int64`. This happens when using either engine but is clearly seen when using `data.to_parquet('example.parquet', engine='fastparquet')`
```
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\fastparquet\writer.py in write_column(f, data, selement, compression)
    447                 if selement.type == parquet_thrift.Type.INT64:
--> 448                     data = data.astype(int)
    449                 elif selement.type == parquet_thrift.Type.BOOLEAN:

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\util\_decorators.py in wrapper(*args, **kwargs)
    176                     kwargs[new_arg_name] = new_arg_value
--> 177             return func(*args, **kwargs)
    178         return wrapper

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\generic.py in astype(self, dtype, copy, errors, **kwargs)
   4996             new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 4997                                          **kwargs)
   4998             return self._constructor(new_data).__finalize__(self)

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\internals.py in astype(self, dtype, **kwargs)
   3713     def astype(self, dtype, **kwargs):
-> 3714         return self.apply('astype', dtype=dtype, **kwargs)
   3715 

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\internals.py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
   3580             kwargs['mgr'] = self
-> 3581             applied = getattr(b, f)(**kwargs)
   3582             result_blocks = _extend_blocks(applied, result_blocks)

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\internals.py in astype(self, dtype, copy, errors, values, **kwargs)
    574         return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 575                             **kwargs)
    576 

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\internals.py in _astype(self, dtype, copy, errors, values, klass, mgr, **kwargs)
    663                 # _astype_nansafe works fine with 1-d only
--> 664                 values = astype_nansafe(values.ravel(), dtype, copy=True)
    665                 values = values.reshape(self.shape)

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\dtypes\cast.py in astype_nansafe(arr, dtype, copy)
    708         if np.issubdtype(dtype.type, np.integer):
--> 709             return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
    710 

pandas\_libs\lib.pyx in pandas._libs.lib.astype_intsafe()

pandas/_libs/src\util.pxd in util.set_value_at_unsafe()

ValueError: invalid literal for int() with base 10: 'Z31'

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-17-6bc14a88da64> in <module>()
----> 1 data.to_parquet('example.parquet', engine='fastparquet')

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\core\frame.py in to_parquet(self, fname, engine, compression, **kwargs)
   1940         from pandas.io.parquet import to_parquet
   1941         to_parquet(self, fname, engine,
-> 1942                    compression=compression, **kwargs)
   1943 
   1944     @Substitution(header='Write out the column names. If a list of strings '

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\io\parquet.py in to_parquet(df, path, engine, compression, **kwargs)
    255     """
    256     impl = get_engine(engine)
--> 257     return impl.write(df, path, compression=compression, **kwargs)
    258 
    259 

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\pandas\io\parquet.py in write(self, df, path, compression, **kwargs)
    216         with catch_warnings(record=True):
    217             self.api.write(path, df,
--> 218                            compression=compression, **kwargs)
    219 
    220     def read(self, path, columns=None, **kwargs):

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\fastparquet\writer.py in write(filename, data, row_group_offsets, compression, file_scheme, open_with, mkdirs, has_nulls, write_index, partition_on, fixed_text, append, object_encoding, times)
    846     if file_scheme == 'simple':
    847         write_simple(filename, data, fmd, row_group_offsets,
--> 848                      compression, open_with, has_nulls, append)
    849     elif file_scheme in ['hive', 'drill']:
    850         if append:

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\fastparquet\writer.py in write_simple(fn, data, fmd, row_group_offsets, compression, open_with, has_nulls, append)
    715                    else None)
    716             rg = make_row_group(f, data[start:end], fmd.schema,
--> 717                                 compression=compression)
    718             if rg is not None:
    719                 fmd.row_groups.append(rg)

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\fastparquet\writer.py in make_row_group(f, data, schema, compression)
    612                 comp = compression
    613             chunk = write_column(f, data[column.name], column,
--> 614                                  compression=comp)
    615             rg.columns.append(chunk)
    616     rg.total_byte_size = sum([c.meta_data.total_uncompressed_size for c in

~\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\fastparquet\writer.py in write_column(f, data, selement, compression)
    453                 raise ValueError('Error converting column "%s" to primitive '
    454                                  'type %s. Original error: '
--> 455                                  '%s' % (data.name, t, e))
    456 
    457     else:

ValueError: Error converting column "B" to primitive type INT64. Original error: invalid literal for int() with base 10: 'Z31'
```

You can see that it is a mixed type column issue if you use `to_csv` and `read_csv` to load data from csv file instead - you get the following warning on import:
```
C:\Users\I347500\AppData\Local\Continuum\miniconda3\envs\work\lib\site-packages\IPython\core\interactiveshell.py:2785: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)
```
Specifying `dtype` option solves the issue but it isn't convenient that there is no way to set column types after loading the data. It is also strange that `to_parquet` tries to infer column types instead of using dtypes as stated in `.dtypes` or `.info()`

#### Expected Output

`to_parquet` tries write parquet file using dtypes as specified

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: None
numpy: 1.14.3
scipy: 1.1.0
pyarrow: 0.9.0
xarray: None
IPython: 6.4.0
sphinx: None
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None
</details>
