7. Matplotlib histogram

Matplotlib can be used to draw a histogram.

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7.1. Python code

The python code is below.

The code is commented to indicate what each part is doing.

import matplotlib.pyplot as plt
import numpy as np
from statistics import median
from pathlib import Path


def plot_histogram(x, title, median):
    # Create a new figure with the specified size
    plt.figure(figsize=(10, 6))
    # Create a histogram plot of the data in x with the specified bin edges, line width, edge color, and fill color
    counts, _, _ = plt.hist(x, bins=np.arange(min(x), max(x)+2), linewidth=0.5, edgecolor="blue", color="lightblue")
    # set the x and y tick locations and labels for the plot to display integer values along both axes, with an offset of 0.5 units for the x tick locations so hte tick is in the middle of each column
    ticks_offset = 0.5
    plt.xticks(np.arange(min(x), max(x)+1) + ticks_offset, np.arange(min(x), max(x)+1))
    plt.yticks(range(0, int(max(counts))+1))
    # Set the x and y axis title labels
    plt.xlabel(title)
    plt.ylabel('Counts')
    # Set the plot title
    plt.title(title)
    # Add a vertical line at the median value with the specified color and line style
    plt.axvline(median + ticks_offset, color="b", linestyle="--")
    # Add a text annotation at the specified x and y coordinates with the specified text, rotation, color, and font size
    plt.text(median + ticks_offset + 0.1, 2, f"Median = {median:.1f}", rotation=90, color="b", fontsize=16)
    # Adjust the margins of the plot to leave space for the axis labels and title
    plt.subplots_adjust(bottom=0.07, left=0.07, top=0.95)
    # Get the directory of the current file
    currfile_dir = Path(__file__).parent
    # Replace spaces in title with underscores to create filename for saving figure
    filename = title.replace(" ", "_")
    # build the image file path
    filepath = currfile_dir / (f"{filename}.png")
    # Save figure (dpi 300 is good when saving so graph has high resolution)
    plt.savefig(filepath, dpi=600)
    # Show the plot on the screen
    plt.show()


def plot_vending_sales():
    # Create a list of data values
    x = [10, 8, 12, 11, 12, 18, 13, 11, 12, 11, 12, 12, 13, 14]
    # Compute the median of the data values
    mymedian = median(x)
    # Set the title of the plot
    title = 'Vending Machine Sales'
    # Call the function to plot the data with the specified title and median value
    plot_histogram(x, title, mymedian)


if __name__ == '__main__':
    plot_vending_sales()