Plotting time-series: putting it all together

In this exercise, you will plot two time-series with different scales on the same Axes, and annotate the data from one of these series.

The CO2/temperatures data is provided as a DataFrame called climate_change. You should also use the function that we have defined before, called plot_timeseries, which takes an Axes object (as the axes argument) plots a time-series (provided as x and y arguments), sets the labels for the x-axis and y-axis and sets the color for the data, and for the y tick/axis labels:

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

Then, you will annotate with text an important time-point in the data: on 2015-10-06, when the temperature first rose to above 1 degree over the average.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

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Exercise instructions

Use the plot_timeseries function to plot CO2 levels against time. Set xlabel to "Time (years)" ylabel to "CO2 levels" and color to 'blue'.
Create ax2, as a twin of the first Axes.
In ax2, plot temperature against time, setting the color ylabel to "Relative temp (Celsius)" and color to 'red'.
Annotate the data using the ax2.annotate method. Place the text ">1 degree" in x=pd.Timestamp('2008-10-06'), y=-0.2 pointing with a gray thin arrow to x=pd.Timestamp('2015-10-06'), y = 1.

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
plot_timeseries(____, ____, ____, 'blue', ____, ____)

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

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

# Annotate point with relative temperature >1 degree
ax2.____(">1 degree", ____, ____, ____)

plt.show()

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