How to Plot Errorbar Charts in Python with Matplotlib

Let’s learn how to plot errorbar using Python library Matplotlib.

Error bars are used to represent the uncertainty or variability of a measurement. They can be used to plot data points with error bars in Python using the Matplotlib library.

Preparation

For start I prepare data and insert common plot.

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]

plt.plot(x, y)
plt.show()

It’s just a common chart. As you can see I have x and y axes populated with values.

Adding errorbar

To plot the error bars, you can use the errorbar() function. The errorbar() function takes the following arguments:

x: The x-coordinates of the data points.
y: The y-coordinates of the data points.
yerr: The error bars.
fmt: The format of the data points.
ecolor: The color of the error bars.

Let’s add error. My measurements are not accurate so some errors may occur.

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', ecolor='red')

plt.show()

I have introduced 0.4 of error. This is how much my values may differ.
To plot errorbar I used errorbar method. Also used some arguments:
– x and y are my values as usual
– yerr is my error
– fmt is formatting and I chose ‘o’ to see my marks as o letters (alternatively you may use x)
– ecolor is the color of my error line and I like red for every error

And this is how my errorbar looks like:

Who told errors has to be the same? You can put different ones for every value.

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = [0.4, 0.2, 1.1, 0.1, 0.4]

plt.errorbar(x, y, yerr=error, fmt='o', ecolor='red')

plt.show()

As you can see the error of 0.3 is very high.

Also you may introduce different values of errors for lower and upper ones. Let’s add min and max values of errors like that:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]

min_error = [0.1, 0.15, 0.12, 0.17, 0.11]
max_error = [0.4, 0.36, 0.44, 0.19, 0.41]
error = [min_error, max_error]

plt.errorbar(x, y, yerr=error, fmt='o', ecolor='red')

plt.show()

I have specified min errors and max errors and defined them under error.

Adding xerr

What if x values are erroneous as well? Then you need to define xerr as well.

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
xerror = 0.02

min_error = [0.1, 0.15, 0.12, 0.17, 0.11]
max_error = [0.4, 0.36, 0.44, 0.19, 0.41]
error = [min_error, max_error]

plt.errorbar(x, y, yerr=error, xerr=xerror, fmt='o', ecolor='red')

plt.show()

You may notice that additional error values appeared for x values.

Plotting Errorbars with Different Colors

In this chapter, we will learn how to plot errorbars with different colors in Python using Matplotlib.

To do this, we can use the `ecolor` argument of the `errorbar()` function. The `ecolor` argument specifies the color of the error bars.

For example, the following code plots the error bars with red color:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', ecolor='red')

plt.show()

The following code plots the error bars with blue color:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', ecolor='blue')
plt.show()

You can also use the `cmap` argument to specify a colormap for the error bars. The `cmap` argument takes a colormap name as its argument.

For example, the following code plots the error bars with a colormap called “viridis”:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', cmap='viridis')
plt.show()

Plotting Errorbars with Different Markers

In this chapter, we will learn how to plot errorbars with different markers in Python using Matplotlib.

To do this, we can use the `fmt` argument of the `errorbar()` function. The `fmt` argument specifies the marker of the data points.

For example, the following code plots the error bars with circle markers:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o')
plt.show()

The following code plots the error bars with square markers:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='s')
plt.show()

You can also use the `markerfacecolor` and `markeredgewidth` arguments to specify the color and width of the marker, respectively.

For example, the following code plots the error bars with red circle markers with a width of 2 pixels:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', markerfacecolor='red', markeredgewidth=2)
plt.show()

Plotting Errorbars with Different Line Styles

In this chapter, we will learn how to plot errorbars with different line styles in Python using Matplotlib.

To do this, we can use the `linestyle` argument of the `errorbar()` function. The `linestyle` argument specifies the line style of the error bars.

For example, the following code plots the error bars with solid line style:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', linestyle='solid')
plt.show()

The following code plots the error bars with dashed line style:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', linestyle='dashed')
plt.show()

You can also use the `linewidth` argument to specify the width of the line.

For example, the following code plots the error bars with a solid line with a width of 2 pixels:

import matplotlib.pyplot as plt

x = [0.1, 0.2, 0.3, 0.4, 0.5]
y = [1.1, 1.4, 1.7, 1.2, 1.25]
error = 0.4

plt.errorbar(x, y, yerr=error, fmt='o', linestyle='solid', linewidth=2)
plt.show()

Now you should know how to insert plot errorbar chart using Python Matplotlib library.

Key Takeaways

• Error bars are used to represent the uncertainty or variability of a measurement.
• Error bars can be plotted in Python using the Matplotlib library.
• The `errorbar()` function is used to plot error bars.
• The `errorbar()` function takes the following arguments:
• `x`: The x-coordinates of the data points.
• `y`: The y-coordinates of the data points.
• `yerr`: The error bars.
• `fmt`: The format of the data points.
• `ecolor`: The color of the error bars.

FAQ

• How do I plot error bars with different colors?

You can use the `ecolor` argument of the `errorbar()` function to specify the color of the error bars.

• How do I plot error bars with different markers?

You can use the `fmt` argument of the `errorbar()` function to specify the marker of the data points.

• How do I plot error bars with different line styles?

You can use the `linestyle` argument of the `errorbar()` function to specify the line style of the error bars.