数据分析

喜欢ヅ旅行 2021-11-11 15:18 258阅读 0赞

**数据分析**

绘制折线图：

![1675683-20190718211546560-429089872.png][]

初步了解matplotlib模块：

from matplotlib import pyplot as plt
    
    x = range(2,26,2)
    y = [15,13,14.5,17,20,25,26,25,27,22,18,15]
    
    # 设置图片大小，figsize设置图片大小，dpi设置分辨率
    plt.figure(figsize=(20,8),dpi=80)
    
    
    
    # 设置x轴刻度
    # plt.xticks(x)
    _xtick_labels = [i/2 for i in range(4,49)]
    plt.xticks(_xtick_labels[::3])
    # 设置y轴刻度
    plt.yticks(range(min(y),max(y)+1))
    
    # 绘图
    plt.plot(x,y)
    
    
    # 展示
    # plt.show()
    
    
    # 保存图片
    plt.savefig('./test.png')

在坐标上加入描述信息，x轴上添加字符串

from matplotlib import pyplot as plt
    from random import randint
    from matplotlib import font_manager
    
    y = [randint(20,40) for i in range(120)]
    x = range(120)
    
    # 设置字体
    # my_font = font_manager.FontEntry(name='C:\Windows\Fonts\MicrosoftYaHeiUI',)   # 报错，不整了
    
    # 设置图片大小
    plt.figure(figsize=(20,8),dpi=80)
    
    # 绘图
    plt.plot(x,y)
    
    # 设置x轴
    _xtick_lables = ['10:{}'.format(i) for i in range(60)]
    _xtick_lables += ['11:{}'.format(i) for i in range(60)]
    
    # 取步长，数字和字符串一一对应，数据长度一样
    plt.xticks(x[::3],_xtick_lables[::3],rotation = 45)
    plt.yticks(range(min(y),max(y)+1))
    
    # 添加描述信息
    plt.xlabel('time')
    plt.ylabel('wendu')
    plt.title('change')
    # 保存
    plt.savefig('./qiwen.png')

绘制表格

from matplotlib import pyplot as plt
    
    y = [1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]
    x = range(11,31)
    
    # 设置图形大小
    plt.figure(figsize=(10,6),dpi=80)
    
    plt.plot(x,y)
    
    # 设置x轴坐标
    _xtick_labels = ['{}y'.format(i) for i in x]
    plt.xticks(x,_xtick_labels)
    
    # 绘制网格
    plt.grid()
    
    # 保存
    plt.savefig('./zhanan.png')

添加图例

from matplotlib import pyplot as plt
    
    y = [1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]
    yy = [1,0,4,1,2,4,4,2,3,4,4,5,5,5,4,3,3,1,6,1]
    x = range(11,31)
    
    # 设置图形大小
    plt.figure(figsize=(10,6),dpi=80)
    
    plt.plot(x,y,label='Mr.Zhao')
    plt.plot(x,yy,label = 'Mr.Qian')
    
    # 设置x轴坐标
    _xtick_labels = ['{}y'.format(i) for i in x]
    plt.xticks(x,_xtick_labels)
    
    # 绘制网格
    plt.grid()
    
    # 添加图例
    plt.legend()
    
    # 保存
    plt.savefig('./zhanan.png')

绘制散点图：

from matplotlib import pyplot as plt
    
    y_3 = [11,17,11,12,22,44,55,21,22,45,22,44,55,11,22,11,34,33,21]
    y_10= [11,18,13,18,24,24,45,23,43,22,24,11,23,13,15,18,43,22,31]
    x_3 = range(1,20)
    x_10 = range(31,50)
    
    
    plt.scatter(x_3,y_3)
    plt.scatter(x_10,y_10)
    
    # plt.figure(figsize=(10,8),dpi=80)
    
    
    plt.xlabel=('time')
    plt.ylabel=('hot')
    plt.title=('qiwen')
    
    plt.grid()
    plt.savefig('./sandian.png')

绘制条形图：

竖着的：

from matplotlib import pyplot as plt
    
    a = ['a1','a2','a3','a4','a5']
    b = [11,20,33,9,40]
    
    plt.bar(range(len(a)),b)
    
    plt.xticks(range(len(a)),[i for i in a])
    
    plt.title('dianying')
    plt.xlabel('x')
    plt.ylabel('y')
    
    plt.figure(figsize=(20,8),dpi=80)
    
    plt.show()

横着的：

from matplotlib import pyplot as plt
    
    a = ['a1','a2','a3','a4','a5']
    b = [11,20,33,9,40]
    
    plt.barh(range(len(a)),b,height=0.3,color='red')
    
    plt.yticks(range(len(a)),[i for i in a])
    
    plt.title('dianying')
    plt.xlabel('x')
    plt.ylabel('y')
    
    plt.grid()
    
    plt.figure(figsize=(20,8),dpi=80)
    
    
    
    plt.show()

多个柱状放在一个表中

from matplotlib import pyplot as plt
    
    x = ['first','secend','third','forth','fith']
    y1= [111,224,899,499,100]
    y2= [444,323,999,888,999]
    y3= [222,333,444,555,666]
    
    x1 = list(range(len(x)))
    x2 = [i+0.2 for i in x1]    # 坐标偏移0.2
    x3 = [i+0.4 for i in x1]
    
    plt.bar(range(len(x)),y1,width=0.2,label='yihao')
    plt.bar(x2,y2,width=0.2,label='erhao')
    plt.bar(x3,y3,width=0.2,label='sanhao')
    
    plt.xticks(x2,x)
    
    plt.legend()
    
    plt.title('movie')
    plt.xlabel('riqi')
    plt.ylabel('piaofang')
    
    plt.show()

直方图：

from matplotlib import pyplot as plt
    
    a = [11,22,33,44,55,66,77,21,23,35,54,32,27,37,47,57]
    
    # 计算组数
    d = 5
    num_bins = (max(a)-min(a))//d
    
    plt.hist(a,num_bins)
    
    plt.xticks(range(min(a),max(a)+d,d))
    
    plt.grid()
    
    plt.show()

转载于:https://www.cnblogs.com/Mr-Feng/p/11208850.html

[1675683-20190718211546560-429089872.png]: /images/20211109/8d2ec81acf63458985bc29dfe7244c4b.png