Exploring openpyxl

# Loop OSM API and create five Excel output files
import pandas as pd
import requests
import json
from itertools import islice
df = pd.read_csv('MoscowMcD.csv')
counterFixed = 0 
counterFixed3 = 3
toggle = 0
excelname = 1
#  Loop through the Open Street Map (OSM) API and calculate the distance and duration of trips between the stores
while counterFixed3 < 16:
    def get_distance(point1: dict, point2: dict): 
        url = f"""http://router.project-osrm.org/route/v1/driving/{point1["lon"]},{point1["lat"]};{point2["lon"]},{point2["lat"]}?overview=false&alternatives=false"""
        r = requests.get(url)
        route = json.loads(r.content)["routes"][0] 
        return (route["distance"], route["duration"])

    listDist = [] 
    for i, r in islice(df.iterrows(), counterFixed, None):
        point1 = {"lat": r["lat"], "lon": r["lon"]}
        if i ==counterFixed3:
            break
        for j, o in df[df.index != i].iterrows():
            point2 = {"lat": o["lat"], "lon": o["lon"]}
            dist, duration = get_distance(point1, point2)
            listDist.append((i, j, duration, dist))
            toggle = 1
    distancesDf = pd.DataFrame(listDist, columns=["From", "To", "Duration(s)", "Distance(m)"])
    distancesDf = distancesDf.merge(df[["Store"]], left_on = "From", right_index=True).rename(columns={"Store":"StartLocation"})
    distancesDf = distancesDf.merge(df[["Store"]], left_on = "To", right_index=True).rename(columns={"Store":"Destination"})
    name = "DistanceStores" + str(excelname)
    filenames = "%s.xlsx" % name # change .csv to .xlsx
    distancesDf.to_excel(filenames, index=False)  # change .to_csv to .to_excel
    counterFixed = counterFixed +3
    counterFixed3 = counterFixed3 +3
    excelname = excelname +1
    # Enter "ls" in the terminal to view the files