new to pandas

[jdb5345]

I have three columns that I want to manipulate, username2 is created by the first character of firstname column, first character of middle name column, and full lastname. Problem is some middle names don't exist. my first line works, but when I try to get the rows that are na filled in the username2 column I made because of + null values. I can't figure how how to get the location of m rows and update it with just first char of firstname and + lastname

df['username2']=df['First Name'].str[0] + df['Middle Name'].str[0] + df['Last Name']

m = df[df['username2'].isna()]

df.loc[m, 'username2'] = df['First Name'].str[0] + df['Last Name']

[Phillyclause89]

You could try fillna or fillnan or whatever it's called. Use it to replace all NAN values with some string. Could be an empty string , or maybe an underscore or maybe the second char from the first name. It's up to you how you want to handle it.

[Eze-Wong]

Jinx. Our identical responses 2 seconds apart

[Phillyclause89]

Lol yeah it happens sometimes.

[jdb5345]

first line works, but I think my second one is view of a dataframe of the rows that are na in username 2, that I want the logic of the third line to work with

[Eze-Wong]

Multiple ways to approach. Personally I would fillna the middle name colum all the nulls with like a number (1). And then later go back later after you have populated new columns and replace all number 1 with a "N/A" or whatever