I have a Pandas dataframe where some rows have missing values (NaN
) in a certain column. I want to drop all the rows where the value in that column is NaN
. How can I do this?
Here’s an example of my dataframe:
This is the output of this code:
A B
0 1 foo
1 2 bar
2 3 None
3 4 baz
As you can see, the value in column B
of row 2 is None
(which is equivalent to NaN
). I want to drop that row.
Here’s the code I’ve tried so far:
df.dropna(subset=['A'], inplace=True)
print(df)
However, this doesn’t seem to work. Can anyone help me figure out what I’m doing wrong here? And are there any alternative ways to drop rows with NaN values in a certain column? Thanks for any help you can provide.