BUG:  downsampling with last doesn't accept "min_count" keyword
I verified this on v 1.1.3. I am on miniconda, 1.1.4 is not available yet. There are ways to install probably but if I read documentation right, this feature should be around since 0.22


```
import numpy as np
import pandas as pd

index = pd.date_range(start='2020', freq='M', periods=6)
data = np.ones(6)
data[4:6] = np.nan
datetime = pd.Series(data, index)
period = datetime.to_period()
datetime
2020-01-31    1.0
2020-02-29    1.0
2020-03-31    1.0
2020-04-30    1.0
2020-05-31    NaN
2020-06-30    NaN
Freq: M, dtype: float64
```

```
datetime.resample('Q').sum(min_count=2)
2020-03-31    3.0
2020-06-30    NaN
Freq: Q-DEC, dtype: float64
```

```
datetime.resample('Q').last(min_count=3)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-bd5dfd934676> in <module>
----> 1 datetime.resample('Q').last(min_count=3)

~\miniconda3\lib\site-packages\pandas\core\resample.py in g(self, _method, *args, **kwargs)
    933 
    934     def g(self, _method=method, *args, **kwargs):
--> 935         nv.validate_resampler_func(_method, args, kwargs)
    936         return self._downsample(_method)
    937 

~\miniconda3\lib\site-packages\pandas\compat\numpy\function.py in validate_resampler_func(method, args, kwargs)
    395             )
    396         else:
--> 397             raise TypeError("too many arguments passed in")
    398 
    399 

TypeError: too many arguments passed in
```



#### Problem description
According to the documentation, .last() does accept the keyword "min_count", just like for example .sum()
where it works fine, see above

So I should not see the error above. The "min_count" is useful also for .last() if you have nans in your data and want to avoid the record that is not truly the last record in the segment.

Doc:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.core.resample.Resampler.last.html#pandas.core.resample.Resampler.last)



#### Expected Output
```
2020-03-31    1.0
2020-06-30    NaN
```

#### Output of ``pd.show_versions()``
See above - verified with pd 1.1.3. I started the issue on my laptop with older pandas but finished with 1.1.3. Error message and pd.show_versions() is up to date

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 8.1
Version          : 6.3.9600
machine          : AMD64
processor        : Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 50.3.1.post20201107
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : 0.49.1


</details>
