import seaborn

df = seaborn.load_dataset("titanic")

df.age.fillna(value=-1, inplace=True)
print(df.head())
print(df.age.isnull().mean()*100)

The output of the above program will be:

   survived  pclass     sex   age  ...  deck  embark_town  alive  alone
0         0       3    male  22.0  ...   NaN  Southampton     no  False
1         1       1  female  38.0  ...     C    Cherbourg    yes  False
2         1       3  female  26.0  ...   NaN  Southampton    yes   True
3         1       1  female  35.0  ...     C  Southampton    yes  False
4         0       3    male  35.0  ...   NaN  Southampton     no   True

[5 rows x 15 columns]
0.0

As we can see, after the arbitrary value imputation in the age column of the dataset, the age column does not have any missing values.