Another approach to an ongoing Python project: reading CSV exported from Calendly to analyze what months students book an advising appointment. Key modules used in this approach include OrderedDict, datetime, and matplotlib.

month_analyzer3.py

import csv
from datetime import datetime
from collections import OrderedDict
import matplotlib.pyplot as plt

# set up empty containers
total = 0
months = dict()

# open and read CSV
with open("dashboard-export.csv") as f:
    csv_reader = csv.reader(f)
    headings = next(csv_reader)
    #convert DATE field to a datetime object and add to months dict
    for row in csv_reader:
        d = row[6].split("/")
        d_obj = datetime(year=int(d[2][0:5]), month=int(d[0]), day=int(d[1]))
        d_obj_month = d_obj.strftime("%B")
        if d_obj_month not in months:
            months[d_obj_month] = 1
        else:
            months[d_obj_month] += 1

# create sorted containers
months_list = sorted(months, key=lambda month: datetime.strptime(month, "%B"))
months_tuples = [(key, months[key]) for key in months_list]
sorted_months_dict = OrderedDict(months_tuples)

# calculate totals and print results
for v in sorted_months_dict.values():
    total += v
for k,v in sorted_months_dict.items():
    print(f"{k} = {v}")
print(f"\ntotal = {total}")

# create lists from dictionary for plotting
appointments = [key for key in sorted_months_dict.keys()]
values = [value for value in sorted_months_dict.values()]

plt.plot(values, color="green")
plt.ylabel("Number of Appts Booked", weight="bold", size="large")
plt.xticks(range(len(values)), appointments, rotation=50, horizontalalignment="right", weight="bold", size="large")
plt.yticks(weight="bold", size="large")
plt.title("Months student book a BAS-SD advising appt with AO", size="large", weight="bold")
plt.show()