Get startedGet started for free

Adding error-bars to a plot

Adding error-bars to a plot is done by using the errorbar method of the Axes object.

Here, you have two DataFrames loaded: seattle_weather has data about the weather in Seattle and austin_weather has data about the weather in Austin. Each DataFrame has a column "MONTH" that has the names of the months, a column "MLY-TAVG-NORMAL" that has the average temperature in each month and a column "MLY-TAVG-STDDEV" that has the standard deviation of the temperatures across years.

In the exercise, you will plot the mean temperature across months and add the standard deviation at each point as y errorbars.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

View Course

Exercise instructions

  • Use the ax.errorbar method to add the Seattle data: the "MONTH" column as x values, the "MLY-TAVG-NORMAL" as y values and "MLY-TAVG-STDDEV" as yerr values.
  • Add the Austin data: the "MONTH" column as x values, the "MLY-TAVG-NORMAL" as y values and "MLY-TAVG-STDDEV" as yerr values.
  • Set the y-axis label as "Temperature (Fahrenheit)".

Hands-on interactive exercise

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

fig, ax = plt.subplots()

# Add Seattle temperature data in each month with error bars
ax.errorbar(____, ____, ____)

# Add Austin temperature data in each month with error bars
____ 

# Set the y-axis label
____

plt.show()
Edit and Run Code