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Let's say I have a DataFrame that looks like this:
a b c d e f g 1 2 3 4 5 6 7 4 3 7 1 6 9 4 8 9 0 2 4 2 1 How would I go about deleting every column besides a and b?
This would result in:
a b 1 2 4 3 8 9 I would like a way to delete these using a simple line of code that says, delete all columns besides a and b, because let's say hypothetically I have 1000 columns of data.
Thank you.
341
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. This gives you a DataFrame with all columns with out one unwanted column.
To select all columns except one column in Pandas DataFrame, we can use df. loc[:, df. columns != <column name>].
We can exclude one column from the pandas dataframe by using the loc function. This function removes the column based on the location. Parameters: dataframe: is the input dataframe.
In [48]: df.drop(df.columns.difference(['a','b']), 1, inplace=True) Out[48]: a b 0 1 2 1 4 3 2 8 9 or:
In [55]: df = df.loc[:, df.columns.intersection(['a','b'])] In [56]: df Out[56]: a b 0 1 2 1 4 3 2 8 9 PS please be aware that the most idiomatic Pandas way to do that was already proposed by @Wen:
df = df[['a','b']] or
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