I feel like I have to apologize in advance for this one, but I've searched for answers and they seem to tell me what I'm doing is correct.

I'm trying to set a DataFrame column to True if another column has instances of a lowercase letter immediately followed by an uppercase letter.

What I tried was this:

    cities['multiteam'] = cities['team'].apply(lambda x: pd.notna(re.search(r'[A][a]',x)))

That's setting all the results to False, so I figured maybe I was doing something wrong with my lambda function and I made the following to debug just the re.search() part:

cities['multiteam'] = pd.notna(re.search(r'[a][A]','OneTwo'))

That's also setting all the results to False. And there I'm stuck.

CodePudding user response：

The following code is useful only to look for a letter 'A' followed by the lower case 'a'.

cities['multiteam'] = cities['team'].apply(lambda t: pd.notna(re.search(r'[A][a]',t)))

You may need to change it if you want to check it for all letters. Maybe replace that line with something like this:

cities['multiteam'] = cities['team'].apply(lambda t: pd.notna(re.search(r'[A-Z][a-z]',t)))

CodePudding user response：

You should never to apologise about asking questions. Using apply is quite slow, try and use the str.contains which can accept a regex pattern.

cities.assign(multiteam=cities.team.str.contains('[a-z][A-Z]'))

The assign above is pandas new recommend way of assigning columns.

The str.contains works with regex and fixed strings, much faster than apply.

The regex pattern above says a range of a-z followed by A-Z.