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Pandas DataFrame | first_valid_index method

schedule Aug 12, 2023
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Pandas DataFrame.first_valid_index(~) method returns the index of the first occurrence of a row containing a non-NaN value. The check is performed row-wise, starting from the first row.

Note that in the following cases, None is returned:

  • if all entries of the source DataFrame are NaN

  • if the source DataFrame is empty

Parameters

This method has no parameters.

Return Value

The row label of the first occurrence of a row containing at least one non-NaN. The returned type hence depends on the index of your DataFrame.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":[np.NaN,3,np.NaN], "B":[np.NaN,np.NaN, 6]}, index=["a","b","c"])
df
A B
a NaN NaN
b 3.0 NaN
c NaN 6.0

The index of the first non-NaN value in the DataFrame is:

df.first_valid_index()
'b'

Here, the output is 'b' because the first row with a non-NaN value has the label of 'b'.

Related

Pandas DataFrame | last_valid_index method
Returns the index of the last occurrence of a non-NaN or non-null value. The check is performed row-wise, starting from the first row.
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Published by Isshin Inada
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Official Pandas Documentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.first_valid_index.html
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