用值分组两列以获得第三列

Question

you'll find two columns Name and N - for most entries both name and N are same

but there are cases where N is missing when Name is present and vice versa

Group the columns such that k I have one resultant column that has all values

Example :

Col1 Col2 value.... 

Adam   nan   334

John    nan   56

nan    Michael  90

Result :

Col1 value.... 

Adam   334

John    56

Michael  90

Answer 1

try this :

for index, row in df.iterrows() :
  if not isinstance(df['col1'][index],str) : 
    df['col1'][index] = df['col2'][index]

knowing that nan is a float, if it finds that the value at 'col1' is nan it will take the value at 'col2'

or using apply

df['B'] = df.apply(lambda x : x['C'] if not isinstance(x['B'],str) else x['B'] ,axis= 1)

new_df = df.delete('C',axis=1)