Get startedGet started for free

Using a plotting function

Defining functions allows us to reuse the same code without having to repeat all of it. Programmers sometimes say "Don't repeat yourself".

In the previous exercise, you defined a function called plot_timeseries:

plot_timeseries(axes, x, y, color, xlabel, ylabel)

that takes an Axes object (as the argument axes), time-series data (as x and y arguments) the name of a color (as a string, provided as the color argument) and x-axis and y-axis labels (as xlabel and ylabel arguments). In this exercise, the function plot_timeseries is already defined and provided to you.

Use this function to plot the climate_change time-series data, provided as a pandas DataFrame object that has a DateTimeIndex with the dates of the measurements and co2 and relative_temp columns.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

View Course

Exercise instructions

  • In the provided ax object, use the function plot_timeseries to plot the "co2" column in blue, with the x-axis label "Time (years)" and y-axis label "CO2 levels".
  • Use the ax.twinx method to add an Axes object to the figure that shares the x-axis with ax.
  • Use the function plot_timeseries to add the data in the "relative_temp" column in red to the twin Axes object, with the x-axis label "Time (years)" and y-axis label "Relative temperature (Celsius)".

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

fig, ax = plt.subplots()

# Plot the CO2 levels time-series in blue
____(____, ____, ____, "blue", ____, ____)

# Create a twin Axes object that shares the x-axis
ax2 = ____

# Plot the relative temperature data in red
____(____, ____, ____, "red", ____, ____)

plt.show()
Edit and Run Code