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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 Ba NaN NaNb 3.0 NaNc 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'`.

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