matpoltlib各种基础图形绘制

Matplotlib绘图教程

最新推荐文章于 2022-11-14 18:04:36 发布

原创最新推荐文章于 2022-11-14 18:04:36 发布 · 275 阅读

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#python

本文详细介绍了使用Python的Matplotlib库进行数据可视化的方法，包括散点图、折线图、条形图、直方图、饼状图、箱形图等图表的绘制，以及子图和多图的布局技巧。

散点图：

import numpy as np
import matplotlib.pyplot as plt

open,high=np.loadtxt('000001.csv',delimiter=',',skiprows=1,usecols=(1,2),unpack=True)

change=high-open

yesterday=change[:-1]
today=change[1:]

plt.scatter(today,yesterday)

折线图：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

x=np.linspace(0,10,100)
y=np.sin(x)
plt.plot(x,y)
plt.show()
date,open,high,low,close=np.loadtxt('000001.csv',delimiter=',',
                                    converters={0:mdates.strpdate2num('%m/%d/%Y')},skiprows=1,usecols=(0,1,2,3,4),unpack=True)
                                    
plt.plot_date(date,open,'y-')

plt.plot_date(date,high,'g-')

plt.plot_date(date,low,'b-')

plt.plot_date(date,close,'r-')

plt.show()

条形图：

import numpy as np
import matplotlib.pyplot as plt

index=np.arange(5)

sales_BJ=[52,55,63,53,40]
sales_SH=[44,66,55,41,30]

bar_width=0.3

plt.barh(left=0,bottom=index,width=sales_BJ,height=bar_width,color='b')
plt.barh(left=0,bottom=index+bar_width,width=sales_SH,height=bar_width,color='r')
plt.show()

plt.barh(left=0,bottom=index,width=sales_BJ,height=bar_width,color='b')
plt.barh(left=sales_BJ,bottom=index,width=sales_SH,height=bar_width,color='r')
plt.show()

直方图：

import numpy as np
import matplotlib.pyplot as plt

mu = 10  # mean of distribution
sigma = 3  # standard deviation of distribution
x = mu + sigma * np.random.randn(2000)

plt.hist(x, bins=10,normed=True)
plt.hist(x, bins=50,normed=False)
plt.show()

x=np.random.randn(2000)+1
y=np.random.randn(2000)+5
plt.hist2d(x,y,bins=40)
plt.show()

饼状图：

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

# Some data

labels = 'SH', 'BJ', 'SZ', 'GD'
fracs = [20, 10, 30, 25]

explode = (0, 0, 0.05, 0)

plt.axes(aspect=1)

plt.pie(fracs, explode=explode, labels=labels, autopct='%.1f%%', shadow=True)

plt.show()

箱形图：

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(100)

data = np.random.normal(size=(100, 5), loc=0.0, scale=1.0)

labels = ['A','B','C','D','E']

plt.boxplot(data, labels=labels,sym='o',whis=1.25)

plt.show()

子图：

import matplotlib.pyplot as plt

plt.subplot(121)
plt.plot(range(12))

plt.subplot(122)
plt.plot([3,2,1],[1,2,3])

plt.show()

多图：

import matplotlib.pyplot as plt

fig1=plt.figure()

ax1=fig1.add_subplot(111)

ax1.plot([1,2,3],[3,2,1])

fig2=plt.figure()

ax2=fig2.add_subplot(111)

ax2.plot([1,2,3],[1,2,3])

plt.show()

图例：

import matplotlib.pyplot as plt
import numpy as np

x=np.arange(1,11,1)
y=x*x

plt.plot(x,x*2,label='Normal')

plt.plot(x,x*3,label='Fast')

plt.plot(x,x*4,label='Faster')

plt.legend()

plt.show()

#方式2

plt.plot(x,x*2)
plt.plot(x,x*3)
plt.plot(x,x*4)

plt.legend(['Normal','Fast','Faster'])

#参数
plt.legend(bbox_to_anchor=(0,1,1,0.1),loc=3,ncol=3,mode="expand")