Assign value to pandas dataframe columns based on condition-CodePudding

i wanted to assign a value on Pandas dataframe based on a condition of the length of the value..

So i wanted to create a new column, that new column value is assigned based on the condition, if the value length is > 8. and another new column is assigned with value =< 8

I'm trying this : So the df_dr_dp_lj['kode_wilayah'] is the existing columns that holds the value, and i wanted to check the length of it. And the columns df_dr_dp_lj['kode_kelurahan'] and that column will hold the value with length more than 8. And this column df_dr_dp_lj['kode_kecamatan'] will hold the value with length =<8 My code is looking like this :

if df_dr_dp_lj['kode_wilayah'].str.len() > 8:
    df_dr_dp_lj['kode_kelurahan']=df_dr_dp_lj['kode_wilayah']
else :
    df_dr_dp_lj['kode_kecamatan']=df_dr_dp_lj['kode_wilayah']

an error i got is :

Input In [47], in <cell line: 1>()
----> 1 if df_dr_dp_lj['kode_wilayah'].str.len() > 8:
      2     df_dr_dp_lj['kode_kelurahan']=df_dr_dp_lj['kode_wilayah']
      3 else :

File D:\Python\lib\site-packages\pandas\core\generic.py:1527, in NDFrame.__nonzero__(self)
   1525 @final
   1526 def __nonzero__(self):
-> 1527     raise ValueError(
   1528         f"The truth value of a {type(self).__name__} is ambiguous. "
   1529         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
   1530     )

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

#update

I tried it with the suggested answer, but still got data length for more than 8 of length.

CodePudding user response：

here is one way to do it, using mask

in your code example, you're using a for loop and doing a comparison against a series, hence the error

df_dr_dp_lj['kode_kelurahan']= df_dr_dp_lj['kode_wilayah'].mask(
    df_dr_dp_lj['kode_wilayah'].str.len()> 8, 
    df_dr_dp_lj['kode_wilayah'] )

df_dr_dp_lj['kode_kecamatan']= df_dr_dp_lj['kode_wilayah'].mask(
    df_dr_dp_lj['kode_wilayah'].str.len()<=8, 
    df_dr_dp_lj['kode_wilayah'] )