CODEWITHSUNDEEP
pythonpandasdataframe
redwolf_cr7
redwolf_cr7

Reputation: 2037

Add a column from one pandas dataframe to another when both are indexed differently

I'm new to python. I have two pandas dataframes that are indexed differently. I want to copy a column from one to another. Dataframe 1: Holds the id and class that each image belongs to

      ID  index  class
0  10472  10472      0
1   7655   7655      0
2   6197   6197      0
3   9741   9741      0
4   9169   9169      0

Dataframe 2: Holds the id of the image in index and the image data in data columns

                                                    data
index                                                   
5882   [[[255, 255, 255, 0], [255, 255, 255, 0], [255...
360    [[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0...
1906   [[[255, 255, 255, 0], [255, 255, 255, 0], [255...
3598   [[[255, 255, 255, 0], [232, 232, 247, 25], [34...
231    [[[255, 255, 255, 0], [234, 234, 234, 0], [57,...

I want to iterate through the dataframe1 and pick up the image id and look up the dataframe 2 for the matching id in the index and copy the 'data' column over to dataframe1. How could i do this (in a performance optimal way)?

Upvotes: 2

Views: 62

Answers (1)

jezrael
jezrael

Reputation: 862661

First for match data need same types, so if get different:

print (df1['index'].dtype)    
int64
print (df2.index.dtype)   
object

there are 2 possible solutions - convert index to integers by:

df2.index = df2.index.astype(int)

Or column to strings:

df1['index'] = df1['index'].astype(str)

Then use map by column data in df2:

df1['data'] = df1['index'].map(df2['data'])

Or if need add multiple columns from df2 (e.g. in real data) use join:

df1 = df1.join(df2, on=['index'])

Upvotes: 2

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