iat returns too much info

I'm trying to create a program that looks for a cell value with a specific name (A1 for example). When it finds it, it takes a value from a cell in the same row and another value from a cell in a different sheet.

my problem is that when I try and use iat[] it returns the value that I want, but with some extra data that I don't know where it gets it from.

import re
import pandas as pd
import csv
import sys

rows = pd.read_excel(r'DSF test.xls', sheet_name='Raw Data', usecols="A")
lr = rows.index[-1]+2

#this is what value you are looking for in the data
for m in ("A"):
    for n in range(1,5):
        well = m+str(n) #this creates A1 for example

        for i in range(0,110):
            dfwell = pd.read_excel(r'DSF test.xls', sheet_name='Raw Data', header=7, usecols="A")
            vrst = dfwell.loc[i].to_string(index=False)
            if vrst == well:
                dfreading = pd.read_excel(r'DSF test.xls', sheet_name='Raw Data', header=7, usecols="F")
                csvreading = dfreading.loc[i].to_string(index=False)
                c = 4
                dftemp = pd.read_excel(r'DSF test.xls', sheet_name='Melt Region Temperature Data', header=7)
                csvtemp = dftemp.iat[i,c]
                c += 1


                csvdata = csvtemp + "," + csvreading

                filename = well + ".csv"
                with open(filename, "a", newline="") as f:
                    thewriter = csv.writer(f)

Also the program is very slow to run but I'm trying to make it do what I want first and I'll optimize it later.

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