BUG: SeriesGroupBy.value_counts() throws IndexError if there is only one group
- [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.

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

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

```python
import pandas as pd
pd.DataFrame([[0, 1]], columns=('a', 'b')).groupby('a')['b'].value_counts()
```
```python-traceback
IndexError                                Traceback (most recent call last)
<ipython-input-53-ab16326ac16f> in <module>
----> 1 pd.DataFrame([[0,1]], columns=('a', 'b')).groupby('a')['b'].value_counts()

~/.venvs/python3/lib/python3.9/site-packages/pandas/core/groupby/generic.py in value_counts(self, normalize, sort, ascending, bins, dropna)
    762         if not len(lchanges):
    763             inc = lchanges
--> 764         inc[idx] = True  # group boundaries are also new values
    765         out = np.diff(np.nonzero(np.r_[inc, True])[0])  # value counts
    766

IndexError: index 0 is out of bounds for axis 0 with size 0
```

#### Problem description

Calling `value_counts()` on a `SeriesGroupBy` throws an `IndexError` when there is only one group.

#### Expected Output

```python
a  b
0  1    1
Name: b, dtype: int64
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : f00ed8f47020034e752baf0250483053340971b0
python           : 3.9.4.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Mon Apr 12 20:57:45 PDT 2021; root:xnu-6153.141.28.1~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
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              : 21.0.1
setuptools       : 54.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.23.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 4.0.0
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
