Using pandas to read a column name differently

Question

I have built a random forest model using sklearn and python to predict 'pages' from various 'size' features. In my testing and training data, the column headers are 'pages' and 'size', but in my new data I want to feed through my model to get the predictions, the column headers are 'p' and 's', rather than 'pages' and 'size'. I was wondering if there is anyway to read these as 'pages' and 'size' so that my model works correctly. Thank you so much!

Does this answer your question? [Renaming columns in pandas](https://stackoverflow.com/questions/11346283/renaming-columns-in-pandas) — Nicolas Gervais, Jun 19 '20 at 17:42

score 0 · Answer 1 · answered Jun 19 '20 at 17:40

0

You can add another column with new name to original dataframe and drop the old ones.

df['p'] = df['pages']

df['s'] = df['sizes']

df = df.drop(['pages','sizes'],axis=1)

answered Jun 19 '20 at 17:40

Vijeth Rai

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instead of doubling the size of the dataframe, then splitting it, you could also just rename the columns – Nicolas Gervais Jun 19 '20 at 17:43
Yes, how do I rename them? – Jun 19 '20 at 17:56

score 0 · Answer 2 · answered Jun 19 '20 at 18:11

0

You can simply use df.rename:

df.rename(columns={'p':'pages', 's', 'sizes'}

I hope this will help you!

answered Jun 19 '20 at 18:11

Emanuele

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Using pandas to read a column name differently

2 Answers2