13、python matplotlib绘制折线图、直方图、条形图、散点图

折线图：显示趋势变化
直方图：显示连续变量分布
条形图：常用于离散型变量，比较数据之间的差别
散点图：反映变量间的关系，展示离群点
一、绘制折线图

import matplotlib.pyplot
import matplotlib.pyplot as plt
from matplotlib import font_manager
import random
x=range(11,31)
y= [1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]
plt.figure(figsize=(20,8),dpi=80)
_xlabel=['{}岁'.format(i) for i in x ]

my_font=font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
plt.xticks(x,_xlabel,fontproperties=my_font)
plt.yticks(range(0,9),fontproperties=my_font)
plt.xlabel('添加x轴标签',fontproperties=my_font)
plt.ylabel('添加y轴标签',fontproperties=my_font)
plt.title('添加标题',fontproperties=my_font)
plt.grid(alpha=0.4)##alpha设置透明度0-1，由xtick、yticks设置网格的疏密
plt.plot(x,y,color='r',linestyle='--',linewidth=10,label='自己')#设置线条参数
y1=[1,0,3,1,2,2,3,3,2,1 ,2,1,1,1,1,1,1,1,1,1]
plt.plot(x,y1,label='他人')###同一张图画的线
plt.legend(loc=1,prop=my_font)###先设置plt.plot中label，loc设置位置，prop设置字体
plt.show()

二、绘制散点图：比较不同条件之间的内联关系，观察数据的离散聚合程度

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager

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)
###设置图片大小透明度
plt.figure(figsize=(20,8),dpi=80)
###绘制散点图
plt.scatter(x_3,y_3,label='3月')
plt.scatter(x_10,y_10,label='10月')
###字体
my_font=font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
####刻度
_x=list(x_3)+list(x_10)
_xticks_label=['3月{}日'.format(i) for i in x_3]+['10月{}日'.format(i) for i in x_3]
plt.xticks(_x[::3],_xticks_label[::3],fontproperties=my_font,rotation=45)
###绘制图例
plt.legend(loc='upper left',prop=my_font)
###绘制标题
plt.xlabel('温度')
plt.ylabel('日期')
###展示图片
plt.show()

三、绘制条形图
1、纵向条形图

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
##字符串+\n 实现换行展示
##a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：\n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",]

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",]
y=[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]
plt.figure(figsize=(20,15),dpi=80)
my_font=font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
###绘制条形图width修改条形图粗细
plt.bar(range(len(a)),y,width=0.7,color='orange')

plt.xticks(range(len(a)),a,fontproperties=my_font,rotation=90)
###保存文件
plt.savefig('movie.png')
plt.show()

2、绘制横向条形图：网格的作用相当于移动坐标轴，便于比较

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
##字符串+\n 实现换行展示
##a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：\n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",]

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",]
y=[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]
plt.figure(figsize=(15,20),dpi=80)
my_font=font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
###绘制条形图width修改条形图粗细
plt.barh(range(len(a)),y,height=0.7,color='orange')

plt.yticks(range(len(a)),a,fontproperties=my_font)
###绘制网格，便于比较大小,相当于移动坐标轴
plt.grid(alpha=0.5)
plt.show()

3、多分组条形图

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager

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]
####控制柱粗细，柱间距为1，所有柱的总宽度不能超过1
barheight=0.2
a_16 = range(len(a))
a_15 =[i+barheight for i in range(len(a))]
a_14 =[i+barheight*2 for i in range(len(a))]
plt.figure(figsize=(15,20),dpi=80)
my_font=font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
plt.barh(a_16,b_16,height=barheight )
plt.barh(a_15,b_15,height=barheight)
plt.barh(a_14,b_14,height=barheight)
plt.yticks(a_15,a,fontproperties=my_font)
plt.show()

四、绘制直方图
1、绘制直方图：没有统计过的数据才可绘制直方图

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import math
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]
bin_width=3
bin_num=math.ceil((max(a)-min(a))/bin_width)
##plt.hist(a,bin_num)##传入组数，组距为(最大值-最小值)/组数
###传入列表，元素为分组依据，组距可以不均匀,density=True绘制频率分布直方图
plt.hist(a,list(range(min(a),max(a)+bin_width,bin_width)))
plt.xticks(list(range(min(a),max(a)+bin_width,bin_width)),rotation=45)
###以上两行与以下两行等价
##plt.hist(a,[min(a)+i*bin_width for i in range(bin_num+1)])
##plt.xticks([min(a)+i*bin_width for i in range(bin_num+1)],rotation=45)
plt.grid(alpha=0.4)
plt.show()

2、统计数据，不等宽条形图画的直方图

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import math

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]
plt.figure(figsize=(20,8),dpi=80)
###默认的刻度为往后移 前一个柱宽的一半
plt.bar(interval,quantity,width)

interval.append(150)
width.insert(0,5)
#plt.xticks(interval)
plt.xticks([i-w*0.5 for i,w in zip(interval,width)],interval)
plt.grid(alpha=0.4)
plt.show()

3、统计数据，等宽条形图画的直方图

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import math

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

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

#plt.xticks(interval)
plt.xticks([i-0.5 for i in range(len(quantity)+1)],interval+[150])
plt.grid(alpha=0.4)
plt.show()

五、画图流程
明确问题、选择图像、准备数据、绘图及完善图形