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I have a dataframe with a lot of columns using the suffix '_o'. Is there a way to drop all the columns that has '_o' in the end of its label?
In this post I've seen a way to drop the columns that start with something using the filter function. But how to drop the ones that end with something?
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We can use Pandas drop() function to drop multiple columns from a dataframe. Pandas drop() is versatile and it can be used to drop rows of a dataframe as well. To use Pandas drop() function to drop columns, we provide the multiple columns that need to be dropped as a list.
Select All Except One Column Using drop() Method in pandas In order to remove columns use axis=1 or columns param. For example df. drop("Discount",axis=1) removes Discount column by kepping all other columns untouched.
You can also use DataFrame. drop() method to delete the last n columns. Use axis=1 to specify the columns and inplace=True to apply the change on the existing DataFrame. On below example df.
Pandonic
df = df.loc[:, ~df.columns.str.endswith('_o')]
df = df[df.columns[~df.columns.str.endswith('_o')]]
List comprehensions
df = df[[x for x in df if not x.endswith('_o')]]
df = df.drop([x for x in df if x.endswith('_o')], 1)
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