BUG: in case of dtype mismatch (int vs category), error message from concat is not crystal clear
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
exi = pd.read_parquet('/home/yoh/Documents/code/data/existing.parquet', engine='fastparquet')
new = pd.read_parquet('/home/yoh/Documents/code/data/new.parquet', engine='fastparquet')
to_record = pd.concat([exi, new])
```

Please, find files enclosed. I could not succeed to re-create manually faulty dataframes.
[faulty_dataframes.zip](https://github.com/pandas-dev/pandas/files/6825097/faulty_dataframes.zip)
(size of each is 5 rows x 8 columns)

#### Problem description

Before installation of `pandas 1.3.0`, I was using `pandas 1.2.5` and `fastparquet 0.6.4.dev0` and this extract of data was not causing problem.
After I installed `pandas 1.3.0`  the `concat` command is now issuing following error:

```python
to_record = pd.concat([exi, new])
Traceback (most recent call last):

  File "<ipython-input-2-9967cb321e9e>", line 4, in <module>
    to_record = pd.concat([exi, new])

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/util/_decorators.py", line 311, in wrapper
    return func(*args, **kwargs)

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/reshape/concat.py", line 307, in concat
    return op.get_result()

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/reshape/concat.py", line 532, in get_result
    new_data = concatenate_managers(

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/internals/concat.py", line 222, in concatenate_managers
    values = _concatenate_join_units(join_units, concat_axis, copy=copy)

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/internals/concat.py", line 486, in _concatenate_join_units
    to_concat = [

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/internals/concat.py", line 487, in <listcomp>
    ju.get_reindexed_values(empty_dtype=empty_dtype, upcasted_na=upcasted_na)

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/internals/concat.py", line 403, in get_reindexed_values
    values = self.block.get_values()

  File "/home/yoh/anaconda3/lib/python3.8/site-packages/pandas/core/internals/blocks.py", line 1360, in get_values
    return np.asarray(values).reshape(self.shape)

ValueError: cannot reshape array of size 5 into shape (1,0)
```

I could notice that using `pyarrow` to read the files back allows having dataframes not causing any error.
I also tried to concat various extract of the dataframes by selecting column one by one, or even several at once, and it does not raise the error. For instance, following ` concat`  do not raise trouble:

```python
to_record = pd.concat([exi[['timestamp','period','side']], new[['side','timestamp','period']]])
to_record = pd.concat([exi[['period','id']], new[['id','period']]])
to_record = pd.concat([exi['tracking'], new['tracking']])
# etc...
```

I am at a loss to reduce the trouble to the root cause.
Please, would anyone has some advice?

#### Expected Output
No error :)

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

<details>

INSTALLED VERSIONS
------------------
commit           : f00ed8f47020034e752baf0250483053340971b0
python           : 3.8.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.8.0-59-generic
Version          : #66~20.04.1-Ubuntu SMP Thu Jun 17 11:14:10 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0
numpy            : 1.20.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.3
setuptools       : 52.0.0.post20210125
Cython           : 0.29.23
pytest           : 6.2.4
hypothesis       : None
sphinx           : 4.0.2
blosc            : None
feather          : None
xlsxwriter       : 1.4.4
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 2021.06.0
fastparquet      : 0.6.4.dev0
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.4.19
tables           : 3.6.1
tabulate         : 0.8.9
xarray           : 0.18.2
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.53.1

</details>
