isin() is ideal if you have a list of exact matches, but if you have a list of partial matches or substrings to look for, you can filter using the str.contains method and regular expressions.
For example, if we want to return a DataFrame where all of the stock IDs which begin with '600' and then are followed by any three digits:
>>> rpt[rpt['STK_ID'].str.contains(r'^600[0-9]{3}$')] # ^ means start of string
... STK_ID ... # [0-9]{3} means any three digits
... '600809' ... # $ means end of string
... '600141' ...
... '600329' ...
... ... ...
Suppose now we have a list of strings which we want the values in 'STK_ID' to end with, e.g.
endstrings = ['01$', '02$', '05$']
We can join these strings with the regex 'or' character | and pass the string to str.contains to filter the DataFrame:
>>> rpt[rpt['STK_ID'].str.contains('|'.join(endstrings)]
... STK_ID ...
... '155905' ...
... '633101' ...
... '210302' ...
... ... ...
Finally, contains can ignore case (by setting case=False), allowing you to be more general when specifying the strings you want to match.
For example,
str.contains('pandas', case=False)
would match PANDAS, PanDAs, paNdAs123, and so on.
