Filter dataframe rows if value in column is in a set list of values

Use the isin method:

rpt[rpt['STK_ID'].isin(stk_list)]

you can also use ranges by using:

b = df[(df['a'] > 1) & (df['a'] < 5)]

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.