BUG: reduction operations failing if `min_count` is larger
- [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
>>> df = pd.DataFrame({"x": [1, 2, 3], "y": [4, 5, 6]})
>>> df
   x  y
0  1  4
1  2  5
2  3  6
>>> df.sum(min_count=10)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/generic.py", line 11067, in sum
    self, axis, skipna, level, numeric_only, min_count, **kwargs
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/generic.py", line 10787, in sum
    "sum", nanops.nansum, axis, skipna, level, numeric_only, min_count, **kwargs
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/generic.py", line 10774, in _min_count_stat_function
    min_count=min_count,
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/frame.py", line 8847, in _reduce
    res, indexer = df._mgr.reduce(blk_func, ignore_failures=ignore_failures)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 354, in reduce
    nbs = blk.reduce(func, ignore_failures)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 400, in reduce
    nb = self.make_block(res_values)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 286, in make_block
    return make_block(values, placement=placement, ndim=self.ndim)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 2732, in make_block
    return klass(values, ndim=ndim, placement=placement)
  File "/nvme/0/pgali/envs/cudfdev/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 143, in __init__
    f"Wrong number of items passed {len(self.values)}, "
ValueError: Wrong number of items passed 1, placement implies 2

```

This actually works in `1.1.5`:

```python
>>> df
   x  y
0  1  4
1  2  5
2  3  6
>>> df.sum(min_count=10)
x   NaN
y   NaN
dtype: float64
```

#### Problem description

Reduction operations like `sum`, `prod`, etc.. are failing when `min_count` is larger in latest pandas, whereas this used to work in `1.1.5`.

#### Expected Output

```python
>>> df
   x  y
0  1  4
1  2  5
2  3  6
>>> df.sum(min_count=10)
x   NaN
y   NaN
dtype: float64
```
#### Output of ``pd.show_versions()``

<details>


INSTALLED VERSIONS
------------------
commit           : 9d598a5e1eee26df95b3910e3f2934890d062caa
python           : 3.7.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-76-generic
Version          : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.1
numpy            : 1.19.5
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 49.6.0.post20210108
Cython           : 0.29.21
pytest           : 6.2.2
hypothesis       : 6.1.1
sphinx           : 3.4.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.20.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.5
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.52.0

</details>
