Pandas's regular expression function result is so strange

[cools0607]

sorry for another question.
I tried to search lots of data from Excel. After importing data to list(data structure).
I tried two methods.
1. using list with re module search.
2. Transfer list --> dataframe and then apply with .str.contains() method
Both of them can be workable. But dataframe is more slower than pandas dataframe. Is it reasonable?
PS: python console shows below user warning

UserWarning: This pattern has match groups. To actually get the groups, use str.extract.
  return func(self, *args, **kwargs)

I wonder if .str.contains includes specified functions just like re module?

Yes str.contains can take regular expression patterns as in the re module.

For example: '^AA' expresses only searching words start with AA.

Yes that would work,Pandas have a lot build in so there is also a str.startswith.
If wonder if something works,then is best to do a test.

import pandas as pd

d = {
    'Quarters' : ['quarter1','quarter2','quarter3','quarter4'],
     'Description': ['AA year', 'BB year', 'CC year', 'AA year'],
     'Revenue': [23.5, 54.6, 5.45, 41.87]
}
df = pd.DataFrame(d)

Test usage:

>>> df[df['Description'].str.contains(r'^AA')]
  Description  Quarters  Revenue
0     AA year  quarter1    23.50
3     AA year  quarter4    41.87
>>> df[df['Description'].str.contains(r'^AA|BB')]
  Description  Quarters  Revenue
0     AA year  quarter1    23.50
1     BB year  quarter2    54.60
3     AA year  quarter4    41.87

>>> # Using str.startswith
>>> df[df['Description'].str.startswith('AA')]
  Description  Quarters  Revenue
0     AA year  quarter1    23.50
3     AA year  quarter4    41.87
>>> df[df['Description'].str.startswith(('AA', 'BB'))]
  Description  Quarters  Revenue
0     AA year  quarter1    23.50
1     BB year  quarter2    54.60
3     AA year  quarter4    41.87