split and merge pandas dataframe based on input column index

Question

I have a pandas dataframe test_df. This dataframe contains 20 columns. I am given a list of column index col_index = [3, 5] for example.

I need to create two separate dataframes

one only including the columns in col_index
other includes all the columns except the columns in col_index

How do I do that?

I understand I can do

new_df = df.iloc[:, 3]

To create a dataframe out of column number 3. But what do I do as in this case I have multiple column numbers to separate out from the main dataframe?

Using python 3

BENY · Accepted Answer · 2019-03-05 23:59:59Z

1

You can do with drop

df1=df.iloc[:,col_index].copy()
df2=df.drop(df1.columns.tolist(),axis=1).copy()

edited Mar 5, 2019 at 23:59

answered Mar 5, 2019 at 23:52

BENY

324k22 gold badges176 silver badges250 bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

bart cubrich Over a year ago

depending on what you are doing with those df you might want to return df1 and df2 as copies, so you don't accidentally edit the main df, of which df1 and df2 are slices.

nad Over a year ago

@Wen-Ben there is a small typo in the 1st line. If you correct that I will mark it as an answer. df1=df.iloc[:,col_index].copy()

Collectives™ on Stack Overflow

split and merge pandas dataframe based on input column index

1 Answer 1

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related