Python Pandas CVS File: Slicing Values and Removing Lines with Missing Values

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I read "data.csv" file and has 2 columns.

For "code" columns, I would like to slice the value string and put back only last 2 digit(alphabet) of code into columns.

For each rows, if either "username" and "code" value is missing, I would like to remove the row from the list.

import pandas as pd

df.to_csv("data.csv")
df = pd.read_csv("data.csv", usecols = ['username, 'code'])
print(dt)

What I have now

username  code
Chris     AB-12-DF
Jake      
Rebecca   JH-34-TY
          LK-49-RT

Expected Output

username  code
Chris     DF    
Rebecca   TY
jupyter-notebook pandas csv python
1 Answers

I'm assuming the empty cells are "" strings:

df = df[~df.eq("").any(axis=1)]
df["code"] = df["code"].str.rsplit("-", n=1).str[-1]
print(df)

Prints:

  username code
0    Chris   DF
2  Rebecca   TY
user_100359850
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