在 Matplotlib 中的条形图中设置不同的误差条颜色
原文:https://www.geesforgeks.org/setting-different-error-bar-colors-in-bar-plot-in-matplotlib/
Python 为我们提供了各种各样的库，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线颜色。
Matplotlib 中的误差线
matplotlib 的各种图，如条形图、折线图都可以使用误差线。误差线用于显示测量或计算值的精度。没有误差线，使用 matplotlib 从一组值创建的图看起来具有高精度或高置信度。
语法:matplotlib.pyplot.error bar(x，y，yerr=None，xerr=None，fmt= "，ecolor=None，elinewidth =None，倾覆= None，barsabove=False，lolims=False，uplims=False，xlolims=False，xuplims=False，errorevery = 1，capthick=None，，data=None，*kwargs)
参数:该方法接受以下描述的参数:
- x，y:这些参数是数据点的水平和垂直坐标。
- ecolor: 此参数为可选参数。它是 errorbar 线条的颜色，默认值为 NONE。
- 埃莉诺:此参数也是可选参数。它是 errorbar 行的线宽，默认值为 NONE。
- 翻船:这个参数也是可选参数。它是误差线的长度，以磅为单位，默认值为 NONE。
- barsabove: 该参数也是可选参数。它包含布尔值“真”，用于在绘图符号上方绘制误差线。其默认值为“假”。
如何在 Matplotlib 中设置条形图中不同的误差条颜色
例 1:
第一步:首先创建一个条形图。
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# 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:
步骤 2: 将误差线添加到每个点:
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# 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:
步骤 3: 在条形图中设置不同的误差线颜色(示例 1):
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# 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线颜色:
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# 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线颜色。
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# 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:
