Plot multiple subplots within a single figure to visualize the shape of grade distribution in various IT courses with Python 3 and Matplotlib.

grade_multi_plot.py

# Corresponding CSV files exported from local SQL Engine.

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

grades_102 = []
grades_201 = []
grades_206 = []
grades_207 = []
grades_219 = []
grades_220 = []

with open("102.csv") as f1, open("201.csv") as f2, open("206.csv") as f3, open("207.csv") as f4, open("219.csv") as f5, open("220.csv") as f6:

        reader1 = csv.DictReader(f1)
        reader2 = csv.DictReader(f2)
        reader3 = csv.DictReader(f3)
        reader4 = csv.DictReader(f4)
        reader5 = csv.DictReader(f5)
        reader6 = csv.DictReader(f6)

        for row in reader1:
                grades_102.append(float(row["GPA"]))
        for row in reader2:
                grades_201.append(float(row["GPA"]))
        for row in reader3:
                grades_206.append(float(row["GPA"]))
        for row in reader4:
                grades_207.append(float(row["GPA"]))
        for row in reader5:
                grades_219.append(float(row["GPA"]))
        for row in reader6:
                grades_220.append(float(row["GPA"]))

# set plot style
plt.style.use("seaborn")

# set up fig and axs
fig, axs = plt.subplots(2,3)

# IT 102 histogram
axs[0,0].hist(grades_102, bins=15, color="#28a745")
axs[0,0].set_title("IT 102 Grades, B893")
axs[0,0].set_xlabel("Grades", fontsize=8)
axs[0,0].set_ylabel("Frequency", fontsize=8)
axs[0,0].set_ylim(0, 24)
axs[0,0].set_yticks(range(0,24, 2))

# IT 201 histogram
axs[0,1].hist(grades_201, bins=15, color="#28a745")
axs[0,1].set_title("IT 201 Grades, B893")
axs[0,1].set_xlabel("Grades", fontsize=8)
axs[0,1].set_ylabel("Frequency", fontsize=8)
axs[0,1].set_ylim(0, 26)
axs[0,1].set_yticks(range(0,26, 2))

# IT 206 histogram
axs[0,2].hist(grades_206, bins=15, color="#28a745")
axs[0,2].set_title("IT 206 Grades, B893")
axs[0,2].set_xlabel("Grades", fontsize=8)
axs[0,2].set_ylabel("Frequency", fontsize=8)
axs[0,2].set_ylim(0, 26)
axs[0,2].set_yticks(range(0,26, 2))

# IT 207 histogram
axs[1,0].hist(grades_207, bins=15, color="#28a745")
axs[1,0].set_title("IT 207 Grades, B893")
axs[1,0].set_xlabel("Grades", fontsize=8)
axs[1,0].set_ylabel("Frequency", fontsize=8)
axs[1,0].set_ylim(0, 8)
axs[1,0].set_yticks(range(0,8))

# IT 219 histogram
axs[1,1].hist(grades_219, bins=15, color="#28a745")
axs[1,1].set_title("IT 219 Grades, B893")
axs[1,1].set_xlabel("Grades", fontsize=8)
axs[1,1].set_ylabel("Frequency", fontsize=8)
axs[1,1].set_ylim(0, 28)
axs[1,1].set_yticks(range(0,28, 2))

# IT 220 histogram
axs[1,2].hist(grades_220, bins=15, color="#28a745")
axs[1,2].set_title("IT 220 Grades, B893")
axs[1,2].set_xlabel("Grades", fontsize=8)
axs[1,2].set_ylabel("Frequency", fontsize=8)
axs[1,2].set_ylim(0, 7)
axs[1,2].set_yticks(range(0,7))

plt.show()