Simple scatter plot

Scatter are a bi-variate visualization technique. They plot each record in the data as a point. The location of each point is determined by the value of two variables: the first variable determines the distance along the x-axis and the second variable determines the height along the y-axis.

In this exercise, you will create a scatter plot of the climate_change data. This DataFrame, which is already loaded, has a column "co2" that indicates the measurements of carbon dioxide every month and another column, "relative_temp" that indicates the temperature measured at the same time.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

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Exercise instructions

Using the ax.scatter method, add the data to the plot: "co2" on the x-axis and "relative_temp" on the y-axis.
Set the x-axis label to "CO2 (ppm)".
Set the y-axis label to "Relative temperature (C)".

Hands-on interactive exercise

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

fig, ax = plt.subplots()

# Add data: "co2" on x-axis, "relative_temp" on y-axis
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# Set the x-axis label to "CO2 (ppm)"
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# Set the y-axis label to "Relative temperature (C)"
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plt.show()

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