无用之学matplotlib

一、matplotlib学习

matplotlib: 最流行的Python底层绘图库，主要做数据可视化图表,名字取材于MATLAB，模仿MATLAB构建

例子1：

# coding=utf-8
from matplotlib import pyplot as plt

x = range(2,26,2)
y = [15,13,14.5,17,20,25,26,26,27,22,18,15]

#设置图片大小
plt.figure(figsize=(20,8),dpi=80)



#绘图
plt.plot(x,y)

#设置x轴的刻度
_xtick_labels = [i/2 for i in range(4,49)]
plt.xticks(range(25,50))
plt.yticks(range(min(y),max(y)+1))

#保存
# plt.savefig("./t1.png")

#展示图形
plt.show()

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图片如下

例子2

# coding=utf-8
from matplotlib import pyplot as plt
import random
import matplotlib
from matplotlib import font_manager

#windws和linux设置字体的放
# font = {'family' : 'MicroSoft YaHei',
#         'weight': 'bold',
#         'size': 'larger'}
# matplotlib.rc("font",**font)
# matplotlib.rc("font",family='MicroSoft YaHei',weight="bold")

#另外一种设置字体的方式
my_font = font_manager.FontProperties(fname="/System/Library/Fonts/PingFang.ttc")

x = range(0,120)
y = [random.randint(20,35) for i in range(120)]

plt.figure(figsize=(20,8),dpi=80)

plt.plot(x,y)

#调整x轴的刻度
_xtick_labels = ["10点{}分".format(i) for i in range(60)]
_xtick_labels += ["11点{}分".format(i) for i in range(60)]
#取步长，数字和字符串一一对应，数据的长度一样
plt.xticks(list(x)[::3],_xtick_labels[::3],rotation=45,fontproperties=my_font) #rotaion旋转的度数

#添加描述信息
plt.xlabel("时间",fontproperties=my_font)
plt.ylabel("温度 单位(℃)",fontproperties=my_font)
plt.title("10点到12点每分钟的气温变化情况",fontproperties=my_font)

plt.show()

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 例子3

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")

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=(20,8),dpi=80)

plt.plot(x,y)

#设置x轴刻度
_xtick_labels = ["{}岁".format(i) for i in x]
plt.xticks(x,_xtick_labels,fontproperties=my_font)
plt.yticks(range(0,9))

#绘制网格
plt.grid(alpha=0.1)

#展示
plt.show()

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例子4

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")

y_1 = [1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]
y_2 = [1,0,3,1,2,2,3,3,2,1 ,2,1,1,1,1,1,1,1,1,1]

x = range(11,31)

#设置图形大小
plt.figure(figsize=(20,8),dpi=80)

plt.plot(x,y_1,label="自己",color="#F08080")
plt.plot(x,y_2,label="同桌",color="#DB7093",linestyle="--")

#设置x轴刻度
_xtick_labels = ["{}岁".format(i) for i in x]
plt.xticks(x,_xtick_labels,fontproperties=my_font)
# plt.yticks(range(0,9))

#绘制网格
plt.grid(alpha=0.4,linestyle=':')

#添加图例
plt.legend(prop=my_font,loc="upper left")

#展示
plt.show()

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例子5

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")
y_3 = [11,17,16,11,12,11,12,6,6,7,8,9,12,15,14,17,18,21,16,17,20,14,15,15,15,19,21,22,22,22,23]
y_10 = [26,26,28,19,21,17,16,19,18,20,20,19,22,23,17,20,21,20,22,15,11,15,5,13,17,10,11,13,12,13,6]

x_3 = range(1,32)
x_10 = range(51,82)

#设置图形大小
plt.figure(figsize=(20,8),dpi=80)

#使用scatter方法绘制散点图,和之前绘制折线图的唯一区别
plt.scatter(x_3,y_3,label="3月份")
plt.scatter(x_10,y_10,label="10月份")

#调整x轴的刻度
_x = list(x_3)+list(x_10)
_xtick_labels = ["3月{}日".format(i) for i in x_3]
_xtick_labels += ["10月{}日".format(i-50) for i in x_10]
plt.xticks(_x[::3],_xtick_labels[::3],fontproperties=my_font,rotation=45)

#添加图例
plt.legend(loc="upper left",prop=my_font)

#添加描述信息
plt.xlabel("时间",fontproperties=my_font)
plt.ylabel("温度",fontproperties=my_font)
plt.title("标题",fontproperties=my_font)
#展示
plt.show()

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例子6

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")


a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：最后的骑士","摔跤吧！爸爸","加勒比海盗5：死无对证","金刚：骷髅岛","极限特工：终极回归","生化危机6：终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：殊死一战","蜘蛛侠：英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]

b=[56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]


#设置图形大小
plt.figure(figsize=(20,15),dpi=80)
#绘制条形图
plt.bar(range(len(a)),b,width=0.7)
#设置字符串到x轴
plt.xticks(range(len(a)),a,fontproperties=my_font,rotation=90)

plt.savefig("./movie.png")

plt.show()

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例子6-2

#绘制横着的条形图
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")


a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：最后的骑士","摔跤吧！爸爸","加勒比海盗5：死无对证","金刚：骷髅岛","极限特工：终极回归","生化危机6：终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：殊死一战","蜘蛛侠：英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]

b=[56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]


#设置图形大小
plt.figure(figsize=(20,8),dpi=80)
#绘制条形图
plt.barh(range(len(a)),b,height=0.3,color="orange")
#设置字符串到x轴
plt.yticks(range(len(a)),a,fontproperties=my_font)

plt.grid(alpha=0.3)
# plt.savefig("./movie.png")

plt.show()

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例子7

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\\Windows\\Fonts\\STHUPO.ttf")


a = ["猩球崛起3：终极之战","敦刻尔克","蜘蛛侠：英雄归来","战狼2"]
b_16 = [15746,312,4497,319]
b_15 = [12357,156,2045,168]
b_14 = [2358,399,2358,362]

bar_width = 0.2

x_14 = list(range(len(a)))
x_15 =  [i+bar_width for i in x_14]
x_16 = [i+bar_width*2 for i in x_14]

#设置图形大小
plt.figure(figsize=(20,8),dpi=80)

plt.bar(range(len(a)),b_14,width=bar_width,label="9月14日")
plt.bar(x_15,b_15,width=bar_width,label="9月15日")
plt.bar(x_16,b_16,width=bar_width,label="9月16日")

#设置图例
plt.legend(prop=my_font)

#设置x轴的刻度
plt.xticks(x_15,a,fontproperties=my_font)

plt.show()

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例子8

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

a=[131,  98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115,  99, 136, 126, 134,  95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117,  86,  95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123,  86, 101,  99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140,  83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144,  83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137,  92,121, 112, 146,  97, 137, 105,  98, 117, 112,  81,  97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112,  83,  94, 146, 133, 101,131, 116, 111,  84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150]

#计算组数
d = 3  #组距
num_bins = (max(a)-min(a))//d
print(max(a),min(a),max(a)-min(a))
print(num_bins)


#设置图形的大小
plt.figure(figsize=(20,8),dpi=80)
plt.hist(a,num_bins,normed=True)

#设置x轴的刻度
plt.xticks(range(min(a),max(a)+d,d))

plt.grid()

plt.show()

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例子9

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

interval = [0,5,10,15,20,25,30,35,40,45,60,90]
width = [5,5,5,5,5,5,5,5,5,15,30,60]
quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]


print(len(interval),len(width),len(quantity))

#设置图形大小
plt.figure(figsize=(20,8),dpi=80)



plt.bar(range(12),quantity,width=1)

#设置x轴的刻度
_x = [i-0.5 for i in range(13)]
_xtick_labels =  interval+[150]
plt.xticks(_x,_xtick_labels)

plt.grid(alpha=0.4)
plt.show()

View Code

 例子9-2

# coding=utf-8
from matplotlib import pyplot as plt
from matplotlib import font_manager

interval = [0,5,10,15,20,25,30,35,40,45,60,90]
width = [5,5,5,5,5,5,5,5,5,15,30,60]
quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]


print(len(interval),len(width),len(quantity))

#设置图形大小
plt.figure(figsize=(20,8),dpi=80)



plt.bar(interval,quantity,width=width)

#设置x轴的刻度

temp_d = [5]+ width[:-1]
_x = [i-temp_d[interval.index(i)]*0.5 for i in interval]


plt.xticks(_x,interval)

plt.grid(alpha=0.4)
plt.show()

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二、常用问题总结

应该选择那种图形来呈现数据
matplotlib.plot(x,y)
matplotlib.bar(x,y)
matplotlib.scatter(x,y)
matplotlib.hist(data,bins,normed)
xticks和yticks的设置
label和titile,grid的设置
绘图的大小和保存图片

做法流程：

　　　　明确问题 选择图形的呈现方式 准备数据 绘图和图形完善

三、推荐网址

　　　　1、matplotlib支持的图形是非常多的，如果有其他的需求，我们 可以查看一下url地址： http://matplotlib.org/gallery/index.html

 　　　　2、plotly:可视化工具中的github,相比于matplotlib更加简单,图形更加漂亮,同时兼容matplotlib和pandas 使用用法:简单,照着文档写即可 文档地址: https://plot.ly/python/

　　　　3、echarts,前端框架，JS

　　　　4、seaborn