CODEWITHSUNDEEP
pythonpandasdataframemerge
Sarang Manjrekar
Sarang Manjrekar

Reputation: 1991

Merging a single column dataframe to another dataframe without having any common key

I have dataframe as below :

                            User_Id     MARKED_CONTENT_AS_FAVOURITE RATE_CONTENT SEARCH VIEWED_CELEBRITY VIEWED_MOVIE VIEWED_TVSHOW
1 6916484f-b7bd-431a-818d-d1a63ff7c717                           0            0      1                0            4             0
2 9fbb7702-5209-46c8-b7c8-2c3d03550b56                           2            2      1                1           20             3
3 cb1fc554-8566-4c9f-a3ca-f64be302d65e                           0            0      1                1            0             0

Now I have a series with just one value. I want to perform a sort of vectorized operation where I have series with only one value.

  USER_CHECKED_IN_CONTENT
3                       0

I want to append this column to the dataframe, as follows.

                               User_Id MARKED_CONTENT_AS_FAVOURITE RATE_CONTENT SEARCH VIEWED_CELEBRITY VIEWED_MOVIE VIEWED_TVSHOW USER_CHECKED_IN_CONTENT
1 6916484f-b7bd-431a-818d-d1a63ff7c717                           0            0      1                0            4             0                       0
2 9fbb7702-5209-46c8-b7c8-2c3d03550b56                           2            2      1                1           20             3                       0
3 cb1fc554-8566-4c9f-a3ca-f64be302d65e                           0            0      1                1            0             0                       0

But when I use 

pivot_activity.append(subset[[x for x in list(subset) if x not in list(pivot_activity)]])

It gives the output as belows :

   MARKED_CONTENT_AS_FAVOURITE  RATE_CONTENT  SEARCH  USER_CHECKED_IN_CONTENT                                User_Id  VIEWED_CELEBRITY  VIEWED_MOVIE 
0                          0.0           0.0     1.0                      NaN   6916484f-b7bd-431a-818d-d1a63ff7c717               0.0           4.0  
1                          2.0           2.0     1.0                      NaN   9fbb7702-5209-46c8-b7c8-2c3d03550b56               1.0          20.0  
2                          0.0           0.0     1.0                      NaN   cb1fc554-8566-4c9f-a3ca-f64be302d65e               1.0           0.0  
2                          NaN           NaN     NaN                      0.0                                    NaN               NaN           NaN

Upvotes: 1

Views: 69

Answers (3)

ak_slick
ak_slick

Reputation: 1016

I think this is what you are going for. A merge does not seem to be what you want since it will have to have some reference to match and you have a 1 to many scenario with differing keys. This code will assign the entire column from the subset data frame's single row single column:

pivot_activity['USER_CHECKED_IN_CONTENT'] = subset[ 'USER_CHECKED_IN_CONTENT'].head(1)

Upvotes: 0

YOLO
YOLO

Reputation: 21729

I think you can use concat here. Let's say you have:

df - bigger data frame
df1 - smaller data frame

You can do: 

pd.concat([df, df1], axis=0).fillna(0)

Upvotes: 0

akshat
akshat

Reputation: 1217

you can add a new column easily to existing dataframe "df" as below:

df['USER_CHECKED_IN_CONTENT'] = 0 # df is your existing dataframe

Upvotes: 1

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