Drop rows of selected rows with null values [duplicate]

Question

I want to drop rows with null values in both column a and b. I have managed to find those rows with:

df[(df['a'].isnull()) & (df['b'].isnull())]

How do I drop these rows?

You just invert the mask: df[~((df['a'].isnull()) & (df['b'].isnull()))] I'm sure this has been answered before, looking for dupe — EdChum
– EdChum, Commented Nov 14, 2017 at 8:42
df.dropna(subset=['a','b'], how='all') really does what I want. And I think its a better approach. Thanks ! — Chia Yi
– Chia Yi, Commented Nov 14, 2017 at 8:58

jezrael · Accepted Answer · 2017-11-14 08:42:08Z

0

Invert mask by ~:

df[~(df['a'].isnull() & df['b'].isnull())]

Or:

df[df[['a','b']].notnull().any(1)]

answered Nov 14, 2017 at 8:42

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

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

1 Comment

Thanks @jezrael ! df.dropna(subset=['a','b'], how='all') does what I want too !