Bar Charts

Part of the Data and Plots section of Coddy's Machine Learning journey. Lesson 26 of 60.

This chapter turns data into summaries. By its end, you will build a two-chart report like this one:

Two charts side by side: a bar chart of average rain for each weekday, Thursday the wettest, and a histogram of daily rain where most days have almost none

It starts with bars. Flavors have no order, so a line from one to the next means nothing. ax.bar(categories, values) draws one bar per category:

flavors = ["Chocolate", "Vanilla", "Mint", "Mango"]
sold = [42, 27, 15, 21]
fig, ax = plt.subplots()
ax.bar(flavors, sold)
ax.set_title("Scoops Sold")
ax.set_ylabel("Scoops")
plt.show()

A bar chart titled Scoops Sold with four bars: Chocolate 42, Vanilla 27, Mint 15, Mango 21

Bars start at 0, so heights compare directly: chocolate's 42 is twice mango's 21. Before training a model, bars of how often each answer appears show whether one dominates.

Challenge

Medium

48 students said how they get to school. counts holds the answers per code: 1 walk, 2 bike, 3 bus, 4 car. To compare schools, chart shares:

Turn the counts into percent, rounded to 1 place (12 of 48 is 25.0).
Draw them as bars: Walk, Bike, Bus, Car.
Label the axis up Students (%).

Yours should look like this, from a smaller school:

A bar chart titled Getting to School with four bars in percent: Walk 26.7, Bike 13.3, Bus 40, Car 20

Your program prints nothing. Coddy describes your bars in the output.

Try it yourself

import numpy as np
import matplotlib.pyplot as plt

# 1 = walk, 2 = bike, 3 = bus, 4 = car
answers = np.array([1, 3, 1, 4, 3, 3, 4, 3, 4, 4, 3, 4, 4, 4, 3, 3,
                    2, 2, 2, 1, 1, 3, 1, 1, 1, 2, 3, 3, 1, 3, 2, 1,
                    3, 4, 3, 3, 1, 1, 1, 2, 3, 1, 3, 4, 4, 3, 2, 4])


# Returns an array: how many values equal each code from 1 to 4
def count_codes(values):
    counts = []
    for code in range(1, 5):
        counts.append((values == code).sum())
    return np.array(counts)


counts = count_codes(answers)
fig, ax = plt.subplots()
ax.set_title("Getting to School")

# Write your code below

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