Setting Different error bar colors in bar plot in Matplotlib

Last Updated : 15 Jan, 2022

Python provides us with a variety of libraries where Matplotlib is one of them. It is used for data visualization purposes. In this article, we will be setting different error bar colors in the bar plot in Matplotlib.

Error bars in Matplotlib

Various plots of matplotlib such as bar charts, line plots can use error bars. Error bars are used for showing the precision in measurements or calculated values. Without Error Bars, the plot created using matplotlib from a set of values looks to be of high precision or high confidence.

Syntax: matplotlib.pyplot.errorbar(x, y, yerr=None, xerr=None, fmt=”, ecolor=None, elinewidth=None, capsize=None, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, errorevery=1, capthick=None, \*, data=None, \*\*kwargs)

Parameters: This method accept the following parameters that are described below:

x, y: These parameters are the horizontal and vertical coordinates of the data points.
ecolor: This parameter is an optional parameter. And it is the color of the errorbar lines with default value NONE.
elinewidth: This parameter is also an optional parameter. And it is the linewidth of the errorbar lines with default value NONE.
capsize: This parameter is also an optional parameter. And it is the length of the error bar caps in points with default value NONE.
barsabove: This parameter is also an optional parameter. It contains boolean value True for plotting errorsbars above the plot symbols.Its default value is False.

How to set different error bar colors in bar plot in Matplotlib

Example 1:

Step 1: Create a bar plot at first.

Python3

# import matplotlib package
import matplotlib.pyplot as plt

# Store set of values in x 
# and height for plotting 
# the graph
x = range(4)
height = [ 3, 6, 5, 4]

# using tuple unpacking
# to grab fig and axes
fig, ax = plt.subplots()

# Creating the bar plot 
# with opacity=0.1
ax.bar(x, height, alpha = 0.1)

Output:

Step 2: Add Error Bar to each of the points:

Python3

# import matplotlib package
import matplotlib.pyplot as plt

# Store set of values in x 
# and height for plotting 
# the graph
x= range(4)
height=[ 3, 6, 5, 4]

# using tuple unpacking
# to grab fig and axes
fig, ax = plt.subplots()

# Creating the bar plot 
# with opacity=0.1
ax.bar(x, height, alpha = 0.1)

# Zip function acts as an
# iterator for tuples so that
# we are iterating through 
# each set of values in a loop

for pos, y, err in zip(x, height, error):
    ax.errorbar(pos, y, err, lw = 2,
                capsize = 4, capthick = 4, 
                color = "green")
    
# Showing the plotted error bar
# plot with same color which is
# green
plt.show()

Output:

Step 3: Setting different error bar colors in the bar plot(Example 1):

Python3

# importing matplotlib
import matplotlib.pyplot as plt

# Storing set of values in
# x, height, error and colors for plotting the graph
x= range(4)
height=[ 3, 6, 5, 4]
error=[ 1, 5, 3, 2]
colors = ['red', 'green', 'blue', 'black']

# using tuple unpacking
# to grab fig and axes
fig, ax = plt.subplots()

# plotting the bar plot
ax.bar( x, height, alpha = 0.1)

# Zip function acts as an
# iterator for tuples so that
# we are iterating through 
# each set of values in a loop
for pos, y, err, colors in zip(x, height, 
                               error, colors):
  
    ax.errorbar(pos, y, err, lw = 2,
                capsize = 4, capthick = 4, 
                color = colors)
    
# Showing the plotted error bar
# plot with different color 
plt.show()

Output:

Example 2: Setting different error bar colors in the bar plot:

Python3

# importing matplotlib package
import matplotlib.pyplot as plt

# importing the numpy package
import numpy as np

# Storing set of values in
# names, x, height, 
# error and colors for plotting the graph
names= ['Bijon', 'Sujit', 'Sayan', 'Saikat']
x=np.arange(4)
marks=[ 60, 90, 55, 46]
error=[ 11, 15, 5, 9]
colors = ['red', 'green', 'blue', 'black']

# using tuple unpacking
# to grab fig and axes
fig, ax = plt.subplots()

# plotting the bar plot
ax.bar(x, marks, alpha = 0.5,
       color = colors)

# Zip function acts as an
# iterator for tuples so that
# we are iterating through 
# each set of values in a loop
for pos, y, err, colors in zip(x, marks,
                               error, colors):
  
    ax.errorbar(pos, y, err, lw = 2,
                capsize = 4, capthick = 4,
                color = colors)
    
# Showing the plotted error bar
# plot with different color 
ax.set_ylabel('Marks of the Students')

# Using x_ticks and x_labels
# to set the name of the
# students at each point
ax.set_xticks(x)
ax.set_xticklabels(names)
ax.set_xlabel('Name of the students')

# Showing the plot
plt.show()

Output:

Example 3: Setting different error bar colors in the bar plot.

Python3

# importing matplotlib
import matplotlib.pyplot as plt

# importing the numpy package
import numpy as np

# Storing set of values in
# names, x, height, error, 
# error1 and colors for plotting the graph
names= ['USA', 'India', 'England', 'China']
x=np.arange(4)
economy=[21.43, 2.87, 2.83, 14.34]
error=[1.4, 1.5, 0.5, 1.9]
error1=[0.5, 0.2, 0.6, 1]
colors = ['red', 'grey', 'blue', 'magenta']

# using tuple unpacking
# to grab fig and axes
fig, ax = plt.subplots()

# plotting the bar plot
ax.bar(x, economy, alpha = 0.5,
       color = colors)

# Zip function acts as an
# iterator for tuples so that
# we are iterating through 
# each set of values in a loop
for pos, y, err,err1, colors in zip(x, economy,
                                    error, error1, 
                                    colors):
  
    ax.errorbar(pos, y, err, err1, fmt = 'o',
                lw = 2, capsize = 4, capthick = 4,
                color = colors)
    
# Showing the plotted error bar
# plot with different color 
ax.set_ylabel('Economy(in trillions)')

# Using x_ticks and x_labels
# to set the name of the
# countries at each point
ax.set_xticks(x)
ax.set_xticklabels(names)
ax.set_xlabel('Name of the countries')

# Showing the plot
plt.show()