在 Matplotlib 的条形图中设置不同的误差条颜色

Python为我们提供了各种库，其中 Matplotlib 就是其中之一。它用于数据可视化目的。在本文中，我们将在 Matplotlib 的条形图中设置不同的误差条颜色。

Matplotlib 中的误差线

matplotlib 的各种图，例如条形图、折线图都可以使用误差线。误差棒用于显示测量或计算值的精度。如果没有误差条，使用 matplotlib 从一组值创建的图看起来具有高精度或高置信度。

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.

如何在 Matplotlib 的条形图中设置不同的误差条颜色

示例 1：

步骤 1：首先创建一个条形图。

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)

输出：

第 2 步：为每个点添加误差条：

蟒蛇3

# 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()

输出：

第 3 步：在条形图中设置不同的误差条颜色（示例 1）：

蟒蛇3

# importing matplotlib
import matplotlib.pyplot as plt
  
# Storing set of values in
# x, height, error and colors for ploting 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()
  
# ploting 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()

输出：

示例 2：在条形图中设置不同的误差条颜色：

蟒蛇3

# 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 ploting 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()
  
# ploting 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()

输出：

示例 3：在条形图中设置不同的误差条颜色。

蟒蛇3

# 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 ploting 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()
  
# ploting 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()

输出：