isnull() and notnull()

>>> print(my_city_series.isnull())

London False

Paris False

Zurich True

Berlin False

Stuttgart True

Hamburg True

dtype: bool

>>> print(my_city_series.notnull())

London True

Paris True

Zurich False

Berlin True

Stuttgart False

Hamburg False

dtype: bool

>>> d = {"a":23, "b":45, "c":None, "d":0}

>>> S = pd.Series(d)

>>> S

a 23.0

b 45.0

c NaN

d 0.0

dtype: float64

We get also a NaN, if a value in the dictionary has a None: