Drop all rows in all columns in pandas dataframe if the value in the column row is zero

Question

I want to drop all rows that are zero in the "feet" column.

df['feet'] = df['feet'][(df != 0).all(1)]


dataset.info()

the above code gives such a result:

col1 8640 non-value object
col2 8640 non-value object
col3 8640 non-value object
col4 8640 non-value object
feet 7640 non-value object

As you can see, the code correctly remove the values in the 'feet' column, but I also want it to delete the rows in all columns where 'feet' = 0

I can do it easily with Numpy but I want to know how it can be done without it.

jezrael · Accepted Answer · 2019-10-18 12:07:36Z

2

df1 = df[df['feet'] != 0]

df1 = df.query("feet != 0")

answered Oct 18, 2019 at 11:58

jezrael

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3 Comments

This is not the point. I want to delete all rows in all columns but only those with zeros in the 'feet' column

@tbone - Sorry, answer was changed.

@ansev - Interesting, I check time of edit and your time of answer and your was one minute later... Not sure why

ansev · Accepted Answer · 2019-10-18 12:06:22Z

1

use this:

df[df['feet'].ne(0)]

or

df[df['feet'] != 0]

or

df[~(df['feet'] == 0)]

df[~(df['feet'].eq(0))]

answered Oct 18, 2019 at 12:06

ansev

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