Annotating a plot of time-series data
Annotating a plot allows us to highlight interesting information in the plot. For example, in describing the climate change dataset, we might want to point to the date at which the relative temperature first exceeded 1 degree Celsius.
For this, we will use the annotate method of the Axes object. In this exercise, you will have the DataFrame called climate_change loaded into memory. Using the Axes methods, plot only the relative temperature column as a function of dates, and annotate the data.
This exercise is part of the course
Introduction to Data Visualization with Matplotlib
Exercise instructions
- Use the
ax.plotmethod to plot the DataFrame index against therelative_tempcolumn. - Use the
annotatemethod to add the text'>1 degree'in the location(pd.Timestamp('2015-10-06'), 1).
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
fig, ax = plt.subplots()
# Plot the relative temperature data
____
# Annotate the date at which temperatures exceeded 1 degree
ax.____(____, ____)
plt.show()