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How can I check the value that exists for the earliest date?

df:

country year index
Turkiye 1992 NaN
Spain 1992 NaN
US 1992 1
Turkiye 1993 1
Spain 1993 1
US 1993 0
Turkiye 1994 1
France 1994 0
Italy 1994 NaN
Turkiye 1995 0

Here, for example, in 1992 Turkiye and Spain are NaNs but the index exists for the US. So I am only interested in the earliest date that the index exists for, the country does not matter in this case.

My code is:

a = np.where(df["Index"]!= None)
a["year"].min()

a is not a data frame, I think for this reason I am having a problem. How can I solve this issue?

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Answer

use .loc with .idxmin after .dropna

df.loc[df.dropna()['year'].idxmin()]


country      US
year       1992
index       1.0
Name: 2, dtype: object
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