Extract Conditional Middle name and last name - pandas

Question

I have a column in a data frame which has a full name as first name, middle name lastname, however for some records no middle name available and want to make sure that it populates the middle name conditionally based on the available pattern but not sure how I can achieve this.
import pandas as pd
name_df = pd.read_csv(r"NameData1.txt",delimiter=",")
splitted_name=name_df.name.str.split(' ',expand=True).fillna('No Value')
##splited_name['middle_name']= splited_name.apply(lambda x : x[1] if x[2] != 'No Value' else '' )
name_df['Middle_name']=name_df.apply(lambda splited_name : splited_name[1] if splited_name[2] != 'No Value' else '')
name_df
I want to display the middle name only when it's there else the last name should be populated.
Sample records:
Id,name
1,TOM M SMITH
2,Gary SMITH
3,John C Doe
4,Hary Knox
5,Rakesh Vaidya
6,John Doe Doe

Answer 1

Use numpy.where for set new column by condition, here are tested None values by Series.isna:
splitted_name=name_df.name.str.split(expand=True)
name_df['First_name'] = splitted_name[0]
name_df['Middle_name']= np.where(splitted_name[2].notna(), splitted_name[1], '')
name_df['Last_name']= np.where(splitted_name[2].notna(), splitted_name[2], splitted_name[1])
print (name_df)
Id name First_name Middle_name Last_name
0 1 TOM M SMITH TOM M SMITH
1 2 Gary SMITH Gary SMITH
2 3 John C Doe John C Doe
3 4 Hary Knox Hary Knox
4 5 Rakesh Vaidya Rakesh Vaidya
5 6 John Doe Doe John Doe Doe

Answer 2

I want to display middle name only wen its there else last name should be populated.
So you can do the below using str.split():
df['middle_or_last']=df.name.apply(lambda x:x.split(' ', maxsplit=len(x.split()))).str[1]
print(df)
Id name middle_or_last
0 1 TOM M SMITH M
1 2 Gary SMITH SMITH
2 3 John C Doe C
3 4 Hary Knox Knox
4 5 Rakesh Vaidya Vaidya
5 6 John Doe Doe Doe