Use DataFrame.apply / Series.apply with a default value for Exceptions

pip install a-pandas-ex-apply-ignore-exceptions

from a_pandas_ex_apply_ignore_exceptions import pd_add_apply_ignore_exceptions

import pandas as pd

pd_add_apply_ignore_exceptions()

df = pd.read_csv(

    "https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv"

)



# the Exception value is the first arg, the rest is just like apply

df1 = df.PassengerId.ds_apply_ignore(pd.NA, lambda x: x / 3)

df2 = df.ds_apply_ignore(pd.NA, lambda x: x["PassengerId"] / 3, axis=1)

df3 = df.PassengerId.ds_apply_ignore(pd.NA, lambda x: x / 0)

df4 = df.ds_apply_ignore(pd.NA, lambda x: x["PassengerId"] / 0, axis=1)

print(df1)

print(df2)

print(df3)

print(df4)





r"""

0        0.333333

1        0.666667

2        1.000000

3        1.333333

4        1.666667

          ...    

886    295.666667

887    296.000000

888    296.333333

889    296.666667

890    297.000000

Name: PassengerId, Length: 891, dtype: float64

0        0.333333

1        0.666667

2        1.000000

3        1.333333

4        1.666667

          ...    

886    295.666667

887    296.000000

888    296.333333

889    296.666667

890    297.000000

Length: 891, dtype: float64

0      <NA>

1      <NA>

2      <NA>

3      <NA>

4      <NA>

       ... 

886    <NA>

887    <NA>

888    <NA>

889    <NA>

890    <NA>

Name: PassengerId, Length: 891, dtype: object

0      <NA>

1      <NA>

2      <NA>

3      <NA>

4      <NA>

       ... 

886    <NA>

887    <NA>

888    <NA>

889    <NA>

890    <NA>

Length: 891, dtype: object



"""