matplotlib学习日记（三）------简单统计图

（一）函数bar（）---------绘制柱状图

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["axes.unicode_minus"] = False

x = [1,2,3,4,5,6,7,8]
y = [3,1,4,5,8,9,2,7]

plt.bar(x,y,align="center",color="c",tick_label = ["q","a","c","e","r","j","b","p"],hatch="-")
'''
align---->对齐方式
tick_label------->标签
hatch-------->填充内容
'''
#设置x,y标签
plt.xlabel("箱子编号")
plt.ylabel("箱子质量（kg）")
plt.show()

（二）函数barh（）--------绘制条形图

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["axes.unicode_minus"] = False

x = [1,2,3,4,5,6,7,8]
y = [3,1,4,5,8,9,2,7]

plt.barh(x,y,align="center",color="c",tick_label = ["q","a","c","e","r","j","b","p"],hatch="/")
'''
align---->对齐方式
tick_label------->标签
hatch-------->填充内容
'''
#设置x,y标签
plt.ylabel("箱子编号")
plt.xlabel("箱子质量（kg）")
plt.show()

（三）函数hist（）-------------绘制直方图

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np


mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["axes.unicode_minus"] = False

boxWeight = np.random.randint(0,10,100)

x = boxWeight

bins = range(0,11,1)

plt.hist(x, bins = bins, color = "g", histtype="bar", rwidth = 1,alpha=.6)

plt.xlabel("箱子质量（kg）")
plt.ylabel("销售数量（个）")

plt.show()

（四）函数pie()---------绘制饼形图

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["axes.unicode_minus"] = False

kinds = "简易箱", "保温箱", "行李箱", "蜜蜂箱"
colors = ["#e41a1c", "#377eb8", "#4daf4a", "#984ea3"]
soldNumbers = [0.0954, 0.4583, 0.1573, 0.3495]

plt.pie(soldNumbers, labels=kinds, autopct="%3.1f%%", startangle=60, colors=colors)
'''
soldNumbers------>传入数据
labels-------->外围标签
autopct----------->精确度
startangle-------->开始角度
colors----------->对应颜色
'''
plt.title("不同种类箱子的销售数量占比")
plt.show()

（五）函数polar（）-----------绘制极线图

import numpy as np
import matplotlib.pyplot as plt

barSlices = 12

theta = np.linspace(0.0, 2*np.pi, barSlices,endpoint=False)#角度
r = 30*np.random.rand(barSlices)#值

plt.polar(theta,r,color="chartreuse",linewidth=5,marker="*",mfc="b",ms=6)
#mfc-------->星的颜色  ms-------->星的大小

plt.show()

（六）函数scatter()------------绘制气泡图，用二维表示三维数据

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

a = np.random.randn(100)
b = np.random.randn(100)

plt.scatter(a, b, s=np.power(10*a+20*b,2),c=np.random.rand(100),cmap=mpl.cm.RdYlBu,marker="o")
'''
a,b为x,y坐标
s---->对应气泡大小
c----->散点标记颜色
cmap----->讲浮点数映射成颜色的颜色映射表
'''
plt.show()

（七）函数stem（）-------绘制棉棒图

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0.5, 2*np.pi, 20)
y = np.random.randn(20)

plt.stem(x, y, linefmt="-.", markerfmt="o", basefmt="--")
'''
x,y------>对应x,y坐标的值
linefmt------>棉棒样式
markerfmt------>棉棒末端样式
basefmt--------->指定基线样式
'''
plt.show()

（八）函数boxplot（）---------绘制箱线图

import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt

mpl.rcParams["font.sans-serif"] = ["FangSong"]
mpl.rcParams["axes.unicode_minus"] = False

x = np.random.randn(1000)

plt.boxplot(x)
plt.xticks([1], ["随机数生成器AlphaRM"])
plt.ylabel("随机数值")
plt.title("随机数生成器抗干扰能力的稳定性")

plt.grid(axis="y", ls=":", lw=1, color="gray", alpha=.4)

plt.show()

（九）函数errorbar()--------绘制误差棒图

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(.1, .6, 6)
y = np.exp(x)

plt.errorbar(x,y,fmt="bo:", yerr=0.2, xerr=.02)

plt.xlim(0, 0.7)
plt.show()