Panda lambda TypeError object float no len()












0















Python Pandas lambda for update column with
lambda x: np.nan if x == '0/0' else df['RatioFraction']



Filter on one column then use lambda to change conditional on np.nan for no vote (0/0).



Received



TypeError: object of type 'float' has no len()


Code:



df['RatioFraction'] = df_ff_reviews['VoteRatio'].apply(lambda x: np.nan if x == '0/0' else df['RatioFraction'])









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  • How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

    – user1857373
    Nov 22 '18 at 5:28
















0















Python Pandas lambda for update column with
lambda x: np.nan if x == '0/0' else df['RatioFraction']



Filter on one column then use lambda to change conditional on np.nan for no vote (0/0).



Received



TypeError: object of type 'float' has no len()


Code:



df['RatioFraction'] = df_ff_reviews['VoteRatio'].apply(lambda x: np.nan if x == '0/0' else df['RatioFraction'])









share|improve this question

























  • How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

    – user1857373
    Nov 22 '18 at 5:28














0












0








0








Python Pandas lambda for update column with
lambda x: np.nan if x == '0/0' else df['RatioFraction']



Filter on one column then use lambda to change conditional on np.nan for no vote (0/0).



Received



TypeError: object of type 'float' has no len()


Code:



df['RatioFraction'] = df_ff_reviews['VoteRatio'].apply(lambda x: np.nan if x == '0/0' else df['RatioFraction'])









share|improve this question
















Python Pandas lambda for update column with
lambda x: np.nan if x == '0/0' else df['RatioFraction']



Filter on one column then use lambda to change conditional on np.nan for no vote (0/0).



Received



TypeError: object of type 'float' has no len()


Code:



df['RatioFraction'] = df_ff_reviews['VoteRatio'].apply(lambda x: np.nan if x == '0/0' else df['RatioFraction'])






python-3.x pandas lambda






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edited Nov 22 '18 at 8:47









Mohit Motwani

1,2151422




1,2151422










asked Nov 22 '18 at 5:25









user1857373user1857373

316




316













  • How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

    – user1857373
    Nov 22 '18 at 5:28



















  • How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

    – user1857373
    Nov 22 '18 at 5:28

















How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

– user1857373
Nov 22 '18 at 5:28





How do I code the apply function, e.g., apply(str.len) inside this lambda function to remove the object type no len()?

– user1857373
Nov 22 '18 at 5:28












2 Answers
2






active

oldest

votes


















0














You can try np.where:



df['RatioFraction'] = np.where(df['VoteRatio'] == '0/0', np.nan, df['VoteRation'])





share|improve this answer































    1














    Try this:



    df['RatioFraction'] = df_ff_reviews['VoteRatio']

    df['RatioFraction'].loc[df['RatioFraction'] == '0/0'] = np.nan





    share|improve this answer























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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      0














      You can try np.where:



      df['RatioFraction'] = np.where(df['VoteRatio'] == '0/0', np.nan, df['VoteRation'])





      share|improve this answer




























        0














        You can try np.where:



        df['RatioFraction'] = np.where(df['VoteRatio'] == '0/0', np.nan, df['VoteRation'])





        share|improve this answer


























          0












          0








          0







          You can try np.where:



          df['RatioFraction'] = np.where(df['VoteRatio'] == '0/0', np.nan, df['VoteRation'])





          share|improve this answer













          You can try np.where:



          df['RatioFraction'] = np.where(df['VoteRatio'] == '0/0', np.nan, df['VoteRation'])






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 22 '18 at 6:20









          Mohit MotwaniMohit Motwani

          1,2151422




          1,2151422

























              1














              Try this:



              df['RatioFraction'] = df_ff_reviews['VoteRatio']

              df['RatioFraction'].loc[df['RatioFraction'] == '0/0'] = np.nan





              share|improve this answer




























                1














                Try this:



                df['RatioFraction'] = df_ff_reviews['VoteRatio']

                df['RatioFraction'].loc[df['RatioFraction'] == '0/0'] = np.nan





                share|improve this answer


























                  1












                  1








                  1







                  Try this:



                  df['RatioFraction'] = df_ff_reviews['VoteRatio']

                  df['RatioFraction'].loc[df['RatioFraction'] == '0/0'] = np.nan





                  share|improve this answer













                  Try this:



                  df['RatioFraction'] = df_ff_reviews['VoteRatio']

                  df['RatioFraction'].loc[df['RatioFraction'] == '0/0'] = np.nan






                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 22 '18 at 5:32









                  AResemAResem

                  1114




                  1114






























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