Applying function on non-null values of two columns in a data frame












0












$begingroup$


I am trying to apply a function on a data frame, the function calculates fuzzy matching and Jellyfish features on two columns. I want this function to do the calculation only on non-null values, even if there is a null in one of the columns.



def feat1(df, col1, col2):

  features = [hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio]

  for j in features:

     df[str.split(col1,sep='_')[0]+'_'+str.split(j,)] = 

       df[[col1,col2]].apply(

         lambda row: j(row[col1], row[col2])

                     if (pd.notnull(row[col1]) & pd.notnull(row[col2])) 

                     else np.NaN,axis=1)


But I am getting the following error:



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'


What's the cause of the error?






python dataframe







share|improve this question











$endgroup$








  • 1




    $begingroup$
    This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
    $endgroup$
    – Mephy
    2 days ago
















0












$begingroup$


I am trying to apply a function on a data frame, the function calculates fuzzy matching and Jellyfish features on two columns. I want this function to do the calculation only on non-null values, even if there is a null in one of the columns.



def feat1(df, col1, col2):

  features = [hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio]

  for j in features:

     df[str.split(col1,sep='_')[0]+'_'+str.split(j,)] = 

       df[[col1,col2]].apply(

         lambda row: j(row[col1], row[col2])

                     if (pd.notnull(row[col1]) & pd.notnull(row[col2])) 

                     else np.NaN,axis=1)


But I am getting the following error:



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'


What's the cause of the error?






python dataframe







share|improve this question











$endgroup$








  • 1




    $begingroup$
    This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
    $endgroup$
    – Mephy
    2 days ago














0












0








0





$begingroup$


I am trying to apply a function on a data frame, the function calculates fuzzy matching and Jellyfish features on two columns. I want this function to do the calculation only on non-null values, even if there is a null in one of the columns.



def feat1(df, col1, col2):

  features = [hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio]

  for j in features:

     df[str.split(col1,sep='_')[0]+'_'+str.split(j,)] = 

       df[[col1,col2]].apply(

         lambda row: j(row[col1], row[col2])

                     if (pd.notnull(row[col1]) & pd.notnull(row[col2])) 

                     else np.NaN,axis=1)


But I am getting the following error:



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'


What's the cause of the error?






python dataframe







share|improve this question











$endgroup$




I am trying to apply a function on a data frame, the function calculates fuzzy matching and Jellyfish features on two columns. I want this function to do the calculation only on non-null values, even if there is a null in one of the columns.



def feat1(df, col1, col2):

  features = [hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio]

  for j in features:

     df[str.split(col1,sep='_')[0]+'_'+str.split(j,)] = 

       df[[col1,col2]].apply(

         lambda row: j(row[col1], row[col2])

                     if (pd.notnull(row[col1]) & pd.notnull(row[col2])) 

                     else np.NaN,axis=1)


But I am getting the following error:



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'



TypeError Traceback (most recent call last) in ----> 1 feat1(dfCart,'FirstName_x','FirstName_y')



in feat1(df, col1, col2) 2 features=[hamming_distance,jaro_winkler,damerau_levenshtein_distance,ratio,partial_ratio,partial_token_set_ratio,partial_token_sort_ratio] 3 for j in features: ----> 4 df[str.split(col1,sep='')[0]+''+str.split(j,)]=df[[col1,col2]].apply(lambda row: j(row[col1],row[col2]) if (pd.notnull(row[col1]) & pd.notnull(row[col2])) else np.NaN,axis=1)



TypeError: descriptor 'split' requires a 'str' object but received a 'builtin_function_or_method'


What's the cause of the error?






python dataframe




python dataframe






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited yesterday









Mephy

683418




683418










asked 2 days ago









GNJGNJ

1




1








  • 1




    $begingroup$
    This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
    $endgroup$
    – Mephy
    2 days ago














  • 1




    $begingroup$
    This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
    $endgroup$
    – Mephy
    2 days ago








1




1




$begingroup$
This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
$endgroup$
– Mephy
2 days ago




$begingroup$
This is probably more suited to StackOverflow. Anyway, I think the problem is the str.split(j,): j is a function, (j,) is an iterable with only a function as a member, and str.split expects an iterable of str. You could adapt your code to have pairs of (distance_function, name): features = [(hamming_distance, 'Hamming distance'), (jaro_winkler, 'Jaro-Winkler'), ...].
$endgroup$
– Mephy
2 days ago










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