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Here is my problem.

I know how to create a boolean column based on RegEx, like this:

df['New Column'] = df.columnA.str.match(regex)

In this example, 'New Column' will be contain True or False values.

But how do I do if I want to use a condition to say "If my RegEx returns true, push "this" value, and if it returns False, then push "that" value.

Thank you for your help :)

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You can use the where() function from NumPy:

df['New Column'] = np.where(df.columnA.str.match(regex), "this", "that")

You can use other column names instead of the scalars:

df['New Column'] = np.where(df.columnA.str.match(regex), df.columnB, df.columnC)
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Hello again @DYZ. How can I do if want to process multiple possibilities and not just a binary condition? How can I use my own function, like for instance "return myfunction(df.columnA)" ? Thank you for your help!
Ok I just made a test and it's easy, I just need to call my function with the column in argument and it works. Pyhon is definitely magic.
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Since you have already got the series of booleans, why not a simple map?

df['New Column'] = list(map(lambda b : 'this' if b else 'that', df.foo.str.match('foo.')))
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Edit:

df['New Column'] = ["this" if row.str.match(regex) else "that" for row in df.columnA]
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