BUG: Series.rolling min_period is ignored and NA behaves strangely
Using current d39a6de668

This may be two separate issues, I can't tell.

### Case 1.

```python
import pandas as pd
ser=pd.Series(range(10))
ser[:5]=None
print(ser)
pd.Series(ser).rolling(3, min_periods=3).count()
```
returns 
```
0    0.0
1    0.0
2    0.0
3    0.0
4    0.0
5    1.0
6    2.0
7    3.0
8    3.0
9    3.0
dtype: float64
```

I expected the first few results to be NA. perhaps related:
```
pd.Series(ser).rolling(3, min_periods=999).count()
```
doesn't raise an exception.

### Case 2.

for series with DatetimeIndex and rolling with an offset, the behavior is also strange, but different.

```python
import pandas as pd
import random
from itertools import chain
dates = ["2001-01-01"]*2 + ["2001-01-02"]*2 + ["2001-01-03"]*2 + ["2001-01-04"]*2 + ["2001-01-05"]*2+ ["2001-01-06"]*2
ser=pd.Series(index=pd.DatetimeIndex(dates))
ser[0]=111
ser[2]=222
ser[6]=333
res=ser.rolling("2D", min_periods=1).count()
df=pd.DataFrame(dict(data=ser,count=res))
print(df)
```

result
```
             data  count
2001-01-01  111.0    1.0   # OK. The day has one non-NA value, 
2001-01-01    NaN    1.0  # and min_period is satisfied
2001-01-02  222.0    2.0  # OK
2001-01-02    NaN    2.0  # OK
2001-01-03    NaN    1.0  # why is this 1.0? this date has no values in it.
2001-01-03    NaN    1.0 # again
2001-01-04  333.0    1.0  # OK
2001-01-04    NaN    1.0 # OK
2001-01-05    NaN    1.0 # why is this 1.0? this date has no values in it.
2001-01-05    NaN    1.0 # again
2001-01-06    NaN    NaN # why is this NaN? min_periods is satisfied
2001-01-06    NaN    NaN # and non-NA count should 0.
```

encountered in the course of #26959