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
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
____
# Set the x-axis label to "CO2 (ppm)"
____
# Set the y-axis label to "Relative temperature (C)"
____
plt.show()