def notnull(self) -> 'DataFrame':
    "\n        Detects non-missing values for items in the current Dataframe.\n\n        This function takes a dataframe and indicates whether it's\n        values are valid (not missing, which is ``NaN`` in numeric\n        datatypes, ``None`` or ``NaN`` in objects and ``NaT`` in datetimelike).\n\n        See Also\n        --------\n        DataFrame.isnull\n\n        Examples\n        --------\n        >>> df = ps.DataFrame([(.2, .3), (.0, None), (.6, None), (.2, .1)])\n        >>> df.notnull()\n              0      1\n        0  True   True\n        1  True  False\n        2  True  False\n        3  True   True\n\n        >>> df = ps.DataFrame([['ant', 'bee', 'cat'], ['dog', None, 'fly']])\n        >>> df.notnull()\n              0      1     2\n        0  True   True  True\n        1  True  False  True\n        "
    return self._apply_series_op((lambda psser: psser.notnull()))
Detects non-missing values for items in the current Dataframe.

This function takes a dataframe and indicates whether it's
values are valid (not missing, which is ``NaN`` in numeric
datatypes, ``None`` or ``NaN`` in objects and ``NaT`` in datetimelike).

See Also
--------
DataFrame.isnull

Examples
--------
>>> df = ps.DataFrame([(.2, .3), (.0, None), (.6, None), (.2, .1)])
>>> df.notnull()
      0      1
0  True   True
1  True  False
2  True  False
3  True   True

>>> df = ps.DataFrame([['ant', 'bee', 'cat'], ['dog', None, 'fly']])
>>> df.notnull()
      0      1     2
0  True   True  True
1  True  False  True
def notnull(self) -> 'DataFrame':
    "\n        Detects non-missing values for items in the current Dataframe.\n\n        This function takes a dataframe and indicates whether it's\n        values are valid (not missing, which is ``NaN`` in numeric\n        datatypes, ``None`` or ``NaN`` in objects and ``NaT`` in datetimelike).\n\n        See Also\n        --------\n        DataFrame.isnull\n\n        Examples\n        --------\n        >>> df = ps.DataFrame([(.2, .3), (.0, None), (.6, None), (.2, .1)])\n        >>> df.notnull()\n              0      1\n        0  True   True\n        1  True  False\n        2  True  False\n        3  True   True\n\n        >>> df = ps.DataFrame([['ant', 'bee', 'cat'], ['dog', None, 'fly']])\n        >>> df.notnull()\n              0      1     2\n        0  True   True  True\n        1  True  False  True\n        "
    return self._apply_series_op((lambda psser: psser.notnull()))