matplotlib绘图实例(一)

淡淡的烟草味﹌ 2023-06-12 11:28 17阅读 0赞

> 作者：lizhonglin  
> github: https://github.com/Leezhonglin/  
> blog: https://leezhonglin.github.io/

#### matplotlib绘图 ####

##### 1.绘制只含有单一曲线 #####

import numpy as np
    import pandas as pd
    from pandas import Series,DataFrame
    import matplotlib.pyplot as plt
    %matplotlib inline
    
    a1 = [20000,26000,30000,36000,45000,55000,56000,58000,57000]
    index1 = [2010,2011,2012,2013,2014,2015,2016,2017,2018]
    data1 = Series(data=a1,index=index1,name='beijing')
    
    
    a2 = [6000,6500,7000,8000,10000,14000,17000,20000,25000]
    index2 = [2010,2011,2012,2013,2014,2015,2016,2017,2018]
    data2 = Series(data=a2,index=index2,name='chengdu')
    # 绘制线形图
    # 需要手动指定X,Y轴的数据
    x = np.linspace(0,2*np.pi,100)
    y = np.sin(x)
    y1 = np.cos(x)
    
    # 在一张图中绘制多条线,需要在一个cell中进行
    # plt会自动引用一个上下文对象(离当前最近的画布对象)
    # 如果写在一起,两个线型图才是使用同一画布
    plt.plot(x,y)
    plt.plot(x,y1)

如下图：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70]

plt.plot(data1.index,data1.values)
    plt.plot(data2.index,data2.values)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 1]

##### 2.设置子画布（坐标系对象） #####

# 注意不是axis
    axes = plt.subplot()
    # axes对象就是当前的子画布对象,可以调用plot的调用方法
    # 绘制线,是画布的方法,所以要使用子画布(坐标系)对象来实现
    axes.plot(data1.index,data1.values)
    axes.plot(data2.index,data2.values)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 2]

# 一个画布中可以存在对个子画布对象
    # 如何设置子画布的位置
    # subplot 
    #1.切分的行数 
    #2.切分的列数 
    #3. 按照前两者的切分方式画子画布的放置位置(从1开始)
    # subplot 参数只是为了描述子画布位置的虚拟数据,并不是真正的把父画布试图进行切割
    # 如果两个子画布有重叠的区间,后绘制的画布会覆盖先绘制的
    # figure对象就是父画布对象, 可以在 figure方法你调整父画布的大小
    axes1 = plt.subplot(3,3,1)
    axes2 = plt.subplot(2,2,4)

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 3]

x = np.linspace(0,3*np.pi,100)
    figure = plt.figure(figsize=(8,5))
    axes3 = plt.subplot(2,2,1)
    axes3.plot(x,np.sin(x))
    axes3.grid(axis='x',linewidth=1)
    
    axes4 = plt.subplot(2,2,2)
    axes4.plot(x,x)
    axes4.grid(color='red')
    
    axes5 = plt.subplot(223)
    axes5.plot(x,np.cos(x))
    axes5.grid(axis='y')
    
    axes6 = plt.subplot(224)
    axes6.plot(x,x**3)
    axes6.grid()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 4]

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[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20191112221203948.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0,size_16,color_FFFFFF,t_70
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[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 3]: https://img-blog.csdnimg.cn/20191112221259490.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0_size_16_color_FFFFFF_t_70 4]: https://img-blog.csdnimg.cn/20191112221321581.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzMzMTk2ODE0,size_16,color_FFFFFF,t_70