Replacing more than one substring value with pandas str.replace

Question

I'm looking for a way to simplify my code:

# Dataset
categorical_data = pd.Series(["dog", "lion", "cat", "crustacean", "dog", "insect", "insect", "cat", "crustacean"])

What I wanna do is to replace dogs, lions & cats with "animal". I can do them by writing this:

categorical_data = categorical_data.str.replace("dog", "animal")
categorical_data = categorical_data.str.replace("cat", "animal")
categorical_data = categorical_data.str.replace("lion", "animal")

Is there a way for the str.replace() function to accept a list of strings instead of just one?

Example:

categorical_data = categorical_data.str.replace([dog, lion, cat], "animal")

Answer 1

For replace by list is possible use Series.replace:

categorical_data = categorical_data.replace(['dog', 'lion', 'cat'], "animal")    
print (categorical_data)
0        animal
1        animal
2        animal
3    crustacean
4        animal
5        insect
6        insect
7        animal
8    crustacean
dtype: object

Difference between answers is with subtrings replacement:

categorical_data = pd.Series(["dog gorilla", "lion", "cat", "crustacean"])

print (categorical_data.replace(['dog', 'lion', 'cat'], "animal"))
0    dog gorilla
1         animal
2         animal
3     crustacean
dtype: object

print (categorical_data.str.replace(r'(dog|cat|lion)', 'animal', regex=True))
0    animal gorilla
1            animal
2            animal
3        crustacean
dtype: object

Answer 2

You could instead use a regex with str.replace, separating the strings to match with | which will be replacing any match among the specified strings:

categorical_data.str.replace(r'(dog|cat|lion)', 'animal', regex=True)

0        animal
1        animal
2        animal
3    crustacean
4        animal
5        insect
6        insect
7        animal
8    crustacean
dtype: object