Errorbar Limit Selection

PythonPythonBeginner
Practice Now

This tutorial is from open-source community. Access the source code

Introduction

In data visualization, it is often necessary to show the degree of uncertainty in the data being plotted. Error bars are a convenient way to represent this uncertainty. In this lab, we will learn how to selectively draw lower and/or upper limit symbols on error bars using the parameters uplims and lolims in Matplotlib.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.


Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlotCustomizationGroup(["`Plot Customization`"]) python(("`Python`")) -.-> python/BasicConceptsGroup(["`Basic Concepts`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/PlottingDataGroup -.-> matplotlib/error_bars("`Error Bars`") matplotlib/PlotCustomizationGroup -.-> matplotlib/legend_config("`Legend Configuration`") python/BasicConceptsGroup -.-> python/booleans("`Booleans`") python/DataStructuresGroup -.-> python/lists("`Lists`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/DataScienceandMachineLearningGroup -.-> python/numerical_computing("`Numerical Computing`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") subgraph Lab Skills matplotlib/importing_matplotlib -.-> lab-48713{{"`Errorbar Limit Selection`"}} matplotlib/figures_axes -.-> lab-48713{{"`Errorbar Limit Selection`"}} matplotlib/error_bars -.-> lab-48713{{"`Errorbar Limit Selection`"}} matplotlib/legend_config -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/booleans -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/lists -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/tuples -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/importing_modules -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/numerical_computing -.-> lab-48713{{"`Errorbar Limit Selection`"}} python/data_visualization -.-> lab-48713{{"`Errorbar Limit Selection`"}} end

Import the necessary libraries

In this step, we import the necessary libraries to create our plots.

import matplotlib.pyplot as plt
import numpy as np

Create the data

In this step, we create the data that we will use to create our error bar plot.

x = np.arange(10)
y = 2.5 * np.sin(x / 20 * np.pi)
yerr = np.linspace(0.05, 0.2, 10)

Create the error bar plot with both limits (default)

In this step, we create an error bar plot with both upper and lower limits, which is the default behavior.

plt.errorbar(x, y + 3, yerr=yerr, label='both limits (default)')

Create the error bar plot with upper limits only

In this step, we create an error bar plot with only upper limits.

plt.errorbar(x, y + 2, yerr=yerr, uplims=True, label='uplims=True')

Create the error bar plot with both upper and lower limits

In this step, we create an error bar plot with both upper and lower limits.

plt.errorbar(x, y + 1, yerr=yerr, uplims=True, lolims=True, label='uplims=True, lolims=True')

Create the error bar plot with subsets of upper and lower limits

In this step, we create an error bar plot with subsets of upper and lower limits.

upperlimits = [True, False] * 5
lowerlimits = [False, True] * 5
plt.errorbar(x, y, yerr=yerr, uplims=upperlimits, lolims=lowerlimits, label='subsets of uplims and lolims')

Create the error bar plot with horizontal error bars

In this step, we create an error bar plot with horizontal error bars.

x = np.arange(10) / 10
y = (x + 0.1)**2

plt.errorbar(x, y, xerr=0.1, xlolims=True, label='xlolims=True')
y = (x + 0.1)**3

plt.errorbar(x + 0.6, y, xerr=0.1, xuplims=upperlimits, xlolims=lowerlimits, label='subsets of xuplims and xlolims')

y = (x + 0.1)**4
plt.errorbar(x + 1.2, y, xerr=0.1, xuplims=True, label='xuplims=True')

Add a legend and show the plot

In this step, we add a legend to the plot and display it.

plt.legend(loc='lower right')
plt.show()

Summary

In this lab, we learned how to selectively draw lower and/or upper limit symbols on error bars using the parameters uplims and lolims in Matplotlib. We also learned how to create error bar plots with horizontal error bars.

Other Python Tutorials you may like