Several Charts in One

Part of the Data and Plots section of Coddy's Machine Learning journey. Lesson 28 of 60.

A food truck tracks its customers and their wait. Different units read best as two charts, side by side in one figure:

Two charts side by side: bars of customers from Monday to Friday, rising to 150 on Friday, and a line of the wait in minutes, rising to 12 on Friday

Busy days, long waits: one glance tells the story. plt.subplots(1, 2) makes 1 row of 2 charts, axs[0] on the left and axs[1] on the right:

days = ["Mon", "Tue", "Wed", "Thu", "Fri"]
customers = [60, 85, 70, 120, 150]
wait = [4, 6, 5, 9, 12]
fig, axs = plt.subplots(1, 2)
axs[0].bar(days, customers)
axs[0].set_title("Customers")
axs[1].plot(days, wait)
axs[1].set_title("Wait (min)")
plt.show()

Each one is a full chart with the methods you know. Rows come first, like a shape: plt.subplots(2, 1) stacks them.

Challenge

Medium

A hiker logged eight hikes: km walked and hours taken. The starter's label(ax, title, xlabel, ylabel) names one chart. Draw two charts side by side:

Left: a line of km (up) per hike number in hikes (across).
Right: one dot per hike, distance across and time up.
Name each chart with one label call, using the texts below.

Yours should look like this one, from another hiker's log:

Two charts side by side: left, a line titled Distance per Hike with Hike across and Distance (km) up; right, dots titled Time vs Distance with Distance (km) across and Time (h) up

The texts: Distance per Hike, Hike, Distance (km) on the left; Time vs Distance, Distance (km), Time (h) on the right. Your program prints nothing.

Try it yourself

import numpy as np
import matplotlib.pyplot as plt

hikes = np.arange(1, 9)
km = np.array([8.0, 12.5, 6.0, 15.0, 10.0, 18.5, 9.5, 14.0])
hours = np.array([2.5, 4.0, 2.0, 5.0, 3.5, 6.5, 3.0, 4.5])


# Gives one chart its title and axis labels (returns nothing)
def label(ax, title, xlabel, ylabel):
    ax.set_title(title)
    ax.set_xlabel(xlabel)
    ax.set_ylabel(ylabel)


# Write your code below

# Don't change the line below
plt.show()