dropna in jan_adjustment will remove all values in row

[pricemg]

precon/precon/adjustments.py

Line 24 in 4e441a7

adjusted = adjusted.dropna()

The above line in the function means if passing in a dataframe with the following format

date	col1	col2
2019-01-01	101	NaN
...	...	...
2019-05-01	104	NaN
2019-06-01	103	100
...	...	...
2020-01-01	101	102

(i.e. col2 timeseries starts later than col1 ) then jan_adjustment will drop the entire row for 2019-01-01.

Not sure on the correct behaviour, but anecdotally removing the dropna seems to work well.