How to compare two str values dataframe python pandas

I am trying to compare two different values in a dataframe. The questions/answers I've found I wasn't able to utilize.

import pandas as pd
# from datetime import timedelta

"""
read csv file
clean date column
convert date str to datetime
sort for equity options
replace date str column with datetime column
"""
trade_reader = pd.read_csv('TastyTrades.csv')
trade_reader['Date'] = trade_reader['Date'].replace({'T': ' ', '-0500': ''}, regex=True)
date_converter = pd.to_datetime(trade_reader['Date'], format="%Y-%m-%d %H:%M:%S")
options_frame = trade_reader.loc[(trade_reader['Instrument Type'] == 'Equity Option')]
clean_frame = options_frame.replace(to_replace=['Date'], value='date_converter')

# Separate opening transaction from closing transactions, combine frames
opens = clean_frame[clean_frame['Action'].isin(['BUY_TO_OPEN', 'SELL_TO_OPEN'])]
closes = clean_frame[clean_frame['Action'].isin(['BUY_TO_CLOSE', 'SELL_TO_CLOSE'])]
open_close_set = set(opens['Symbol']) & set(closes['Symbol'])
open_close_frame = clean_frame[clean_frame['Symbol'].isin(open_close_set)]

'''
convert Value to float
sort for trade readability
write
'''
ocf_float = open_close_frame['Value'].astype(float)
ocf_sorted = open_close_frame.sort_values(by=['Date', 'Call or Put'], ascending=True)
# for readability, revert back to ocf_sorted below
ocf_list = ocf_sorted.drop(
    ['Type', 'Instrument Type', 'Description', 'Quantity', 'Average Price', 'Commissions', 'Fees', 'Multiplier'], axis=1
    )
ocf_list.reset_index(drop=True, inplace=True)
ocf_list['Strategy'] = ''
# ocf_list.to_csv('Sorted.csv')

# create strategy list
debit_single = []
debit_vertical = []
debit_calendar = []
credit_vertical = []
iron_condor = []

# shift columns
ocf_list['Symbol Shift'] = ocf_list['Underlying Symbol'].shift(1)
ocf_list['Symbol Check'] = ocf_list['Underlying Symbol'] == ocf_list['Symbol Shift']

# compare symbols, append depending on criteria met
for row in ocf_list:
    if row['Symbol Shift'] is row['Underlying Symbol']:
        debit_vertical.append(row)

print(type(ocf_list['Underlying Symbol']))
ocf_list.to_csv('Sorted.csv')
print(debit_vertical)
# delta = timedelta(seconds=10)

The error I get is:

line 51, in <module>
    if row['Symbol Check'][-1] is row['Underlying Symbol'][-1]:
TypeError: string indices must be integers

I am trying to compare the newly created shifted column to the original, and if they are the same, append to a list. Is there a way to compare two string values at all in python? I've tried checking if Symbol Check is true and it still returns an error about str indices must be int. .iterrows() didn't work

Solution

Here, you will actually iterate through the columns of your DataFrame, not the rows:

for row in ocf_list:
    if row['Symbol Shift'] is row['Underlying Symbol']:
        debit_vertical.append(row)

You can use one of the methods iterrows or itertuples to iterate through the rows, but they return rows as lists and tuples respectively, which means you can't index them using the column names, as you did here.

Second, you should use == instead of is since you are probably comparing values, not identities.

Lastly, I would skip iterating over the rows entirely, as pandas is made for selecting rows based on a condition. You should be able to replace the aforementioned code with this:

debit_vertical = ocf_list[ocf_list['Symbol Shift'] == ocf_list['Underlying Symbol']].values.tolist()