Q:

Can re.search() skip past integer objects?

Question is pretty self-explanatory. I have a column in a pandas dataframe that contains both int and str objects. When I attempt to search it with re.search() it can't run because (I believe) some of the columns contain integer and it doesn't know what to do.
Is there some type of a way to fix this? I do not see an ignore errors argument.

A:

Best thing to do would be to use pandas inbuilt pandas.Series.str.match Docs. It automatically "skips" int values by casting them all to string.
import pandas as pd
df = pd.DataFrame(data={
                    'Col1': [...],
                    'Col2': [...]}
                 )
df['Col1'].str.match("*pattern*")

You can adjust your pattern to make sure that none of your int strings are matched.
>>> import pandas as pd
>>> df = pd.DataFrame(data={
                    'Col1': ["a string", "a second string", 123, 456, "another string"],
                    'Col2': [1, 2, 3, 4, 5]}
                 )
>>> df['Col1'].str.match("[^0-9]+")
0    True
1    True
2     NaN
3     NaN
4    True
Name: Col1, dtype: object

