Matplotlib: Error Bar Rendering on Polar Axis

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Introduction

In data visualization, error bars are used to indicate the uncertainty or variability of data points. Matplotlib is a popular data visualization library in Python that provides built-in support for error bars. In this lab, we will learn how to create error bar plots in polar coordinates using Matplotlib.

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Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) 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`") 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-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} matplotlib/figures_axes -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} matplotlib/error_bars -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} python/tuples -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} python/importing_modules -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} python/numerical_computing -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} python/data_visualization -.-> lab-48873{{"`Matplotlib: Error Bar Rendering on Polar Axis`"}} end

Import Necessary Libraries

In this step, we will import the necessary libraries for creating error bar plots on polar axes.

import matplotlib.pyplot as plt
import numpy as np

Create Data

In this step, we will create the data for our error bar plot. We will use NumPy to create an array of theta values and an array of corresponding radius values.

theta = np.arange(0, 2 * np.pi, np.pi / 4)
r = theta / np.pi / 2 + 0.5

Create a Figure and Subplot

In this step, we will create a figure and subplot for our error bar plot.

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(projection='polar')

Create Error Bars

In this step, we will create error bars on our polar axis. We will use the errorbar() function to create both radius and theta error bars.

ax.errorbar(theta, r, xerr=0.25, yerr=0.1, capsize=7, fmt="o", c="seagreen")

Set Title and Show Plot

In this step, we will set a title for our plot and show it using the show() function.

ax.set_title("Pretty Polar Error Bars")
plt.show()

Create Overlapping Theta Error Bars

In this step, we will create overlapping theta error bars to demonstrate how they can reduce readability of the output plot.

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(projection='polar')
ax.errorbar(theta, r, xerr=5.25, yerr=0.1, capsize=7, fmt="o", c="darkred")
ax.set_title("Overlapping Theta Error Bars")
plt.show()

Create Large Radius Error Bars

In this step, we will create large radius error bars to demonstrate how they can lead to unwanted scale in the data, reducing the displayed range.

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(projection='polar')
ax.errorbar(theta, r, xerr=0.25, yerr=10.1, capsize=7, fmt="o", c="orangered")
ax.set_title("Large Radius Error Bars")
plt.show()

Summary

In this lab, we learned how to create error bar plots in polar coordinates using Matplotlib. We created a figure and subplot, and used the errorbar() function to create radius and theta error bars. We also demonstrated how overlapping theta error bars can reduce readability, and how large radius error bars can lead to unwanted scale in the data.

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