Encoding time by color
The screen only has two dimensions, but we can encode another dimension in the scatter plot using color. Here, we will visualize the climate_change dataset, plotting a scatter plot of the "co2" column, on the x-axis, against the "relative_temp" column, on the y-axis. We will encode time using the color dimension, with earlier times appearing as darker shades of blue and later times appearing as brighter shades of yellow.
This exercise is part of the course
Introduction to Data Visualization with Matplotlib
Exercise instructions
- Using the
ax.scattermethod add a scatter plot of the"co2"column (x-axis) against the"relative_temp"column. - Use the
ckey-word argument to pass in the index of the DataFrame as input to color each point according to its date. - Set the x-axis label to
"CO2 (ppm)"and 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", "relative_temp" as x-y, index as color
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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()