Dates vs Derivatives

Challenge¶

Thirty college students were surveyed on

1. the number of derivatives they've calculated in the past year and
2. the number of dates they've been on in the past year

import random
 
random.seed(1)
derivatives = [random.randrange(0, 250) for i in range(30)]
dates = [random.randrange(0, max(50 - d, 3)) for d in derivatives]
 
print(derivatives)
# [34, 145, 216, ..., 178, 114, 68]
 
print(dates)
# [7, 2, 0, ..., 0, 1, 2]

Build a scatter plot of this data with

• derivatives on the x axis and dates on y axis (with labeled axes)

• points using the color 'tab '

• the title:

  Dates vs Derivatives
  (for 30 college students surveyed about their recent year)

Solution¶

import matplotlib.pyplot as plt
 
# Instantiate a figure and an Axes
fig, ax = plt.subplots()
 
# Draw a scatter plot on the axes
ax.plot(derivatives, dates, c="tab:red", linestyle='None', marker='o')
 
# Draw the title and labels
ax.set_title("Dates vs Derivatives\n(for 30 college students surveyed about their recent year)")
ax.set_xlabel("derivates")
ax.set_ylabel("dates")

Explanation¶

1. Make a figure with an Axes.

   fig, ax = plt.subplots()

   pyplot.subplots() is a handy function for creating a figure and a set of subplots in a single line. The default behavior creates a single figure with a single Axes, but if we wanted, we could make a grid of Axes with something like this.

   fig, ax = plt.subplots(nrows=3, ncols=3)

   

   Alternatively, we could create the figure and axes in a less cryptic (but lengthier) way, like this.

   fig = plt.figure()  # make the figure
   fig.add_subplot()   # add the subplot
   ax = fig.axes[0]    # get the Axes object (for downstream changes)

   Note that ax is technically an AxesSubplot.

   type(ax)
   # <class 'matplotlib.axes._subplots.AxesSubplot'>

   AxesSubplot is a subclass of the more generic Axes class.

2. Draw a scatter plot on the Axes.

   ax.plot(derivatives, dates, c="tab:red", linestyle='None', marker='o')

   Here we use the Axes.plot() method, passing in derivatives, dates, c="tab:red" (color), linestyle='None', and marker='o'. By default, Axes.plot() connects points with lines (i.e. it draws a line plot). By setting linestyle='None' and marker='o', we get a scatter plot.

   What about Axes.scatter()

   It's true, ax.scatter(x=derivatives, y=dates, c="tab:red") works, but it's less performant than ax.plot(x=derivatives, y=dates, c="tab:red", linestyle='None').

   Use Axes.scatter() when you want to customize the points (e.g. varying their sizes or colors by another variable).

   "tab " stands for Tableau red. See the Tableau color palette here.

   You can find a list of additional matplotlib color palettes here.

3. Draw the title and labels.

   title = "Dates vs Derivatives\n(for 30 college students surveyed about their recent year)"
   ax.set_title(title)        # (1)!
   ax.set_xlabel("derivates") # (2)!
   ax.set_ylabel("dates")     # (3)!

   1. See Axes.set_title()
   2. See Axes.set_xlabel()
   3. See Axes.set_ylabel()

Solution 2 (PyPlot)¶

# Make a scatter plot
plt.scatter(x=derivatives, y=dates, c="tab:red")
 
# Draw the title and labels
plt.title("Dates vs Derivatives\n(for 30 college students surveyed about their recent year)")
plt.xlabel("derivates")
plt.ylabel("dates")

Explanation¶

This solution uses the matplotlib.pyplot state-based interface to matplotlib, with methods:

• pyplot.scatter() (to draw the scatter plot)
• pyplot.title() (to set the title)
• pyplot.xlabel() (to set the x label)
• pyplot.ylabel() (to set the y label)