python - Create a column combining the first and last name columns with a condition-CodePudding

Iam trying to create a new column (fullname) comprising of the first and familyname based on a condition that if the name column is not empty then the strings in the name column should be replaced in the name column and if the name column is empty , then the first and familyname should be joined and replaced in the the name column

this is how the sample data would look like;

   name         |   firstname      | familyname 
kim humphrey    |    NaN           |    NaN
 NaN            |  moustafa        |   elkashlan
 NaN            |   Joey           |    Lamp

i tried writing a python code below df_total['Full_Name'] = np.where(df_total[['FAMILYNAME', 'FIRSTNAME']].eq('').any(axis='index'), df_total['NAME'], df_total[['FAMILYNAME', 'FIRSTNAME']].apply(' '.join, axis='index')).all(axis=1)

Though the folloing error was returned; `TypeError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_24080/1087141216.py in <module> 1 df_total['Full_Name'] = np.where(df_total[['FAMILYNAME', 'FIRSTNAME']].eq('NaN').any(axis='index'), 2 df_total['NAME'], ----> 3 df_total[['FAMILYNAME', 'FIRSTNAME']].apply(' '.join, axis='index')).all(axis=1)

~\anaconda3\lib\site-packages\pandas\core\frame.py in apply(self, func, axis, raw, result_type, args, **kwargs) 8738 kwargs=kwargs, 8739 ) -> 8740 return op.apply() 8741 8742 def applymap(

~\anaconda3\lib\site-packages\pandas\core\apply.py in apply(self) 686 return self.apply_raw() 687 --> 688 return self.apply_standard() 689 690 def agg(self):

~\anaconda3\lib\site-packages\pandas\core\apply.py in apply_standard(self) 810 811 def apply_standard(self): --> 812 results, res_index = self.apply_series_generator() 813 814 # wrap results

~\anaconda3\lib\site-packages\pandas\core\apply.py in apply_series_generator(self) 826 for i, v in enumerate(series_gen): 827 # ignore SettingWithCopy here in case the user mutates --> 828 results[i] = self.f(v) 829 if isinstance(results[i], ABCSeries): 830 # If we have a view on v, we need to make a copy because

TypeError: sequence item 0: expected str instance, float found`

indicated below would be my desired output.

full_name         |  name         |   firstname      | familyname 
kim humphrey      |kim humphrey   |    NaN           |    NaN
moustafa elkashlan|NaN            |  moustafa        |   elkashlan
Joey Lamp         |NaN            |   Joey           |    Lamp

CodePudding user response：

The code below splits it into two assignment steps: providing values for the indexes of the new column where the name column is not null, and another for where they are null.

mask = df_total['name'].notnull()
df_total.loc[mask, 'full_name'] = df_total.loc[mask, 'name']
df_total.loc[~mask, 'full_name'] = df_total[~mask, 'firstname'].astype(str)   " "   df_total[~mask, 'lastname'].astype(str)

Your approach is sound, but the issue is the .eq(''). NaN does not equal an empty string, and it is a float value instead of a string value, hence the error you're receiving. .isnull() may be the condition you're looking for instead:

df_total['full_name'] = np.where(
    df_total[['firstname','familyname']].isnull().any(axis=1),
    df_total['name'],
    df_total[['firstname', 'familyname']].apply(" ".join, axis=1)
)