BUG: ValueError: buffer source array is read-only during groupby
- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd
df = pd.DataFrame(data={'x': [1], 'y': [2]})
df.to_parquet('pq_df', partition_cols='x')
df = pd.read_parquet('pq_df')
df.groupby('x', sort=False)

```

#### Problem description

The above code raises an exception:

```
Traceback (most recent call last):
  File "mve.py", line 5, in <module>
    df.groupby('x', sort=False)
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/frame.py", line 5798, in groupby
    return groupby_generic.DataFrameGroupBy(
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 402, in __init__
    grouper, exclusions, obj = get_grouper(
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/groupby/grouper.py", line 615, in get_grouper
    Grouping(
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/groupby/grouper.py", line 312, in __init__
    self.grouper, self.all_grouper = recode_for_groupby(
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/groupby/categorical.py", line 72, in recode_for_groupby
    cat = cat.add_categories(c.categories[~c.categories.isin(cat.categories)])
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 4667, in isin
    return algos.isin(self, values)
  File "/Users/ehasse/.local/lib/python3.8/site-packages/pandas/core/algorithms.py", line 447, in isin
    return f(comps, values)
  File "pandas/_libs/hashtable_func_helper.pxi", line 555, in pandas._libs.hashtable.ismember_int64
  File "stringsource", line 658, in View.MemoryView.memoryview_cwrapper
  File "stringsource", line 349, in View.MemoryView.memoryview.__cinit__
ValueError: buffer source array is read-only
```

This specifically requires the following:
* The dataframe is loaded from a parquet file.
* The column being grouped by was used to partition the file.
* sort=False is passed.

In addtion, passing observed=True stops the error from occurring.

I believe this is related to #31710, but they were unable to provide an example for groupby, and the issue remains on 1.0.3.

#### Expected Output

A DataFrameGroupBy object.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.0.0.post20200309
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.16.0
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : 0.47.0

</details>
