Visualize exam grades by creating histograms with Plotly.

exam-grades-histogram.ipynb

exam-grades-histogram.py

import plotly.graph_objects as go
import numpy as np

with open('grades.txt', 'r') as f:
    exam_grades = f.readlines()

# convert the strings into integers and assign them to a new list
grades = [int(grade) for grade in exam_grades]

tick_vals = ['[0, 10)', '[10, 20)', '[20, 30)', '[30, 40)', '[40, 50)', '[50, 60)', '[60, 70)', '[70, 80)', '[80, 90)',
             '[90, 100)', '[100, 110)']

for i in range(len(tick_vals)):
    tick_vals[i] = '    ' + tick_vals[i]

# Initialize a dictionary to hold the counts for each bin
histogram = [0] * 11
bins = []
# Count the scores in each bin
for s in grades:
    for b in range(0, 12):
        bin = b * 10
        bins.append(bin + 1)
        if bin <= s < bin + 10:
            histogram[b] += 1

# Create a trace for the bar plot
trace = go.Bar(
    x=bins,  # the bin edges are the x-values, but we don't want to include the rightmost edge
    y=histogram,
    text=['{} ({:.1f}%)'.format(count, count / sum(histogram) * 100) for count in histogram],
    # show count and percentage
    textposition='auto',
    hoverinfo='none',
    width=10,  # set the width of the bars
    marker={'color': bins,
            'colorscale': 'rdylgn'}
)

# Calculate the statistics to be displayed in the legend
min_score = min(grades)
max_score = max(grades)
mean = sum(grades) / len(grades)
median = np.median(grades)
mode = max(histogram)

# Create the layout for the plot
layout = go.Layout(
    xaxis=dict(
        showticklabels=True,
        tick0=0,
        nticks=10,
        dtick=10,
        tickangle=0,
        showgrid=False,
        tickmode='array',
        tickvals=[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110],
        ticktext=tick_vals
    ),
    yaxis=dict(title='Count'),  # set the y-axis title
    bargap=0,  # set the gap between the bars
)

# Create a table trace for the statistics
table_trace = go.Table(
    header=dict(values=['Statistic', 'Value']),  # set the column names
    cells=dict(values=[['Minimum', 'Maximum', 'Mean', 'Median', 'Mode'], [min_score, max_score, mean, median, mode]]),
)

print(f"Min: {min_score:.2f} Max: {max_score:.2f} Mean: {mean:.2f} Median: {median:.2f}")

# Create the figure and plot
fig = go.Figure(data=[trace], layout=layout)
fig.update_layout(
    title_text="Exam Grades",
    font_family="Arial",
    font_size=18,
    title_font_family="Arial",
    title_font_color="black",
    legend_title_font_color="black"
)
fig.show()

grades.txt

95
90
85
85
77
65
65
63
60
60
58
55
55
52
50
50
40
40
40
40
35
35
32
32
32
30
30
30
30
27
27
27
27
25
25
25
25
25
25
25
25
25
22
20
20
20
20
20
15
15
15
12
10
10
10
10
10
10
10
10
10
5
5
5
5
5
5
1