Fine-tuning matplotlib bar plot of Calendly appointment data. Ongoing Python 3 project.

month_analyzer_bar_plot.py

import csv
import calendar
from collections import Counter
import matplotlib.pyplot as plt

# set up empty Counter objectS
months_counter = Counter()

# open and read CSV
with open("dashboard-export.csv") as f:
    csv_reader = csv.DictReader(f)
    for row in csv_reader:
        items = row["Start Date & Time"].split("/")
        m = int(items[0])
        months_counter[m] += 1

# sort Counter into dict
months_dict = dict(sorted(months_counter.items()))

# extract appointment date into two lists
months = [key for key in months_dict.keys()]
values = [value for value in months_dict.values()]

# prepare bar graph
plt.style.use("seaborn")
fig, ax = plt.subplots()
plt.xticks(months, calendar.month_name[1:13], rotation=20)
plot = ax.bar(months, values, color="#28a745")

# display data value on head of each bar
for rect in plot:
    height = rect.get_height()
    ax.text(rect.get_x() + rect.get_width() / 2, 1.002 * height,
            f"{int(height)}", ha="center", va="bottom")

# add ylim, y axis label and title
ax.set_ylim(0, 60)
ax.set_ylabel("No. of Appointments Booked")
plt.title("Snapshot of BAS-SD advising appts booked with AO: July 2017 to PRESENT",
          size="large", weight="bold")

# plot!
plt.show()