I have a DataFrame where I would like to keep the rows when a particular variable has a NaN
value and drop the non-missing values.
Example:
ticker opinion x1 x2
aapl GC 100 70
msft NaN 50 40
goog GC 40 60
wmt GC 45 15
abm NaN 80 90
In the above DataFrame, I would like to drop all observations where opinion is not missing (so, I would like to drop the rows where ticker is aapl, goog, and wmt
).
Is there anything in pandas that is the opposite to .dropna()
?
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