Computing the first non-missing value from each column in a DataFrame [duplicate]

Answer 1

The built in function DataFrame.groupby().column.first() returns the first non null value in the column, while last() returns the last.

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.GroupBy.first.html

If you don't wish to get the first value for each group, you can add a dummy column of 1s. Then get the first non null value using the groupby & first functions.

from Pandas import DataFrame

df = DataFrame({'a':[None,1,None],'b':[None,2,None]})
df['dummy'] = 1
df.groupby('dummy').first()
df.groupby('dummy').last()