Updating A Dataframe Based On Another Dataframe
Given DataFrame df: Id Sex Group Time Time! 0 21 M 2 2.31 NaN 1 2 F 2 2.29 NaN and update: Id Sex Group Time 0 21 M 2 2.36 1 2 F
Solution 1:
I think I would do this with a merge, and then update the columns with a where. First remove the Time column from up:
In [11]: times = up.pop('Time')# up = the update DataFrame
In [12]: df1 = df.merge(up, how='outer')
In [13]: df1
Out[13]:
Id Sex Group Time Time!021 M 22.31NaN12F22.29NaN23F1NaNNaN
Update Time if it's not NaN and Time! if it's NaN:
In [14]: df1['Time!'] = df1['Time'].where(df1['Time'].isnull(), times)
In [15]: df1['Time'] = df1['Time'].where(df1['Time'].notnull(), times)
In [16]: df1
Out[16]:
Id Sex GroupTimeTime!021 M 22.312.3612 F 22.292.0923 F 11.79 NaN
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