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  3. Introduction to Data Visualization with Matplotlib

Exercise

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.

Instructions

100 XP
  • 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)".