Checking if particular value (in cell) is NaN in pandas DataFrame not working using ix or iloc

Question

Lets say I have following pandas DataFrame:

import pandas as pd
df = pd.DataFrame({\"A\":[1,pd.np.nan,2], \"B\":[5,6,0]})
         


        

Answer 1

pd.isna(cell_value) can be used to check if a given cell value is nan. Alternatively, pd.notna(cell_value) to check the opposite.

From source code of pandas:

def isna(obj):
    """
    Detect missing values for an array-like object.

    This function takes a scalar or array-like object and indicates
    whether values are missing (``NaN`` in numeric arrays, ``None`` or ``NaN``
    in object arrays, ``NaT`` in datetimelike).

    Parameters
    ----------
    obj : scalar or array-like
        Object to check for null or missing values.

    Returns
    -------
    bool or array-like of bool
        For scalar input, returns a scalar boolean.
        For array input, returns an array of boolean indicating whether each
        corresponding element is missing.

    See Also
    --------
    notna : Boolean inverse of pandas.isna.
    Series.isna : Detect missing values in a Series.
    DataFrame.isna : Detect missing values in a DataFrame.
    Index.isna : Detect missing values in an Index.

    Examples
    --------
    Scalar arguments (including strings) result in a scalar boolean.

    >>> pd.isna('dog')
    False

    >>> pd.isna(np.nan)
    True