使用Python统计函数绘制复杂图形matplotlib

一、堆积图

1、堆积柱状图

如果将函数bar()中的参数bottom的取值设定为列表y、列表y1代表另一个数，函数bar(x,y1,bottom=y,color="r")就会输出堆积柱状图

代码示例：

import matplotlib.pyplot as plt

x = [1,2,3,4,5]
y = [6,10,4,5,1]
y1 = [2,6,3,8,5]

plt.bar(x,y,align="center",color="#66c2a5",tick_label=["A","B","C","D","E"],label="title_A")
plt.bar(x,y1,align="center",color="#8da0cb",tick_label=["A","B","C","D","E"],label="title_B")
plt.legend()

plt.show()

图像输出：

2、堆积条状图

如果将函数barh()中的参数left的取值设定为列表y，列表y1代表另一数据，函数bar(x,y1,left=y,color="r")

代码示例：

import matplotlib.pyplot as plt

x = [1,2,3,4,5]
y = [6,10,4,5,1]
y1 = [2,6,3,8,5]

plt.barh(x,y,align="center",color="#66c2a5",tick_label=["A","B","C","D","E"],label="title_A")
plt.barh(x,y1,align="center",left=y,color="#8da0cb",tick_label=["A","B","C","D","E"],label="title_B")
plt.legend()

plt.show()

 图像输出：

二、分块图

 1、多数据并列柱状图

代码示例：

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(5)
y = [6,10,4,5,1]
y1 = [2,6,3,8,5]

bar_width = 0.35
tick_label = ["A","B","C","D","E"]
plt.bar(x,y,align="center",color="c",width=bar_width,label="title_A",alpha=0.5)
plt.bar(x+bar_width,y1,align="center",color="b",width=bar_width,label="title_B",alpha=0.5)

plt.xticks(x+bar_width/2,tick_label)
plt.legend()

plt.show()

输出图像：

2、多数据平行条状图

代码示例：

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(5)
y = [6,10,4,5,1]
y1 = [2,6,3,8,5]

bar_width = 0.35
tick_label = ["A","B","C","D","E"]
plt.barh(x,y,bar_width,align="center",color="c",label="title_A",alpha=0.5)
plt.barh(x+bar_width,y1,bar_width,align="center",color="b",label="title_B",alpha=0.5)

plt.yticks(x+bar_width/2,tick_label)
plt.legend()

plt.show()

 输出图像：

三、堆积折线图、间断条形图和阶梯图

1、函数stackplot() —— 绘制堆积折线图

代码示例：

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(