Calculation of first item in the exponential weighted mean ( EWM)
https://github.com/pandas-dev/pandas/blob/1700680381bdbfbc1abe9774f96881801b24d6ca/pandas/core/generic.py#L10159-L10166

Running this code  :

` pd.DataFrame({'B': [1,20,400,1,1,1]}).ewm(span=2,min_periods=2,adjust=False).mean().values.flatten()`
I  am getting
`array([ nan, 13.66666667, 271.22222222,  91.07407407, 31.02469136,  11.00823045])`

As I understand the first item should be the simple moving average with window equals to span ( here it is 2 ). See for example see this link : https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_averages

> There are three steps to calculating an exponential moving average (EMA). First, calculate the simple moving average for the initial EMA value. An exponential moving average (EMA) has to start somewhere, so a simple moving average is used as the previous period's EMA in the first calculation. 

so instead of 13.66666 it should be (20+1)/2 =>10.5

Afterwards the formula is :
![image](https://user-images.githubusercontent.com/3207061/52234883-5ae5ea00-28cb-11e9-90c3-d6ce312d27c8.png)

The formula also can be found here : http://pandas.pydata.org/pandas-docs/stable/user_guide/computation.html  when adjust is set to False .


What do you think ?

Thanks,
Boris