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matplotlib库绘制条形图

时间:2019-07-08 13:59:30      阅读:202      评论:0      收藏:0      [点我收藏+]

练习一:假设你获取到了2017年内地电影票房前20的电影(列表a)和电影票房数据(列表b),那么如何更加直观的展示该数据?

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]

 1 from matplotlib import pyplot as plt
 2 import matplotlib
 3 
 4 """绘制条形图"""
 5 font = {family: MicroSoft YaHei}
 6 matplotlib.rc(font, **font)  # 使支持中文
 7 
 8 x = ["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",]
 9 
10 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]
11 
12 plt.figure(figsize=(20, 8), dpi=80)  # 设置图形大小
13 
14 # plt.bar(range(len(x)), y, width=0.3)  # 绘制条形图,线条宽度
15 plt.barh(range(len(x)), y, height=0.3, color=orange)  # 绘制横着的条形图,横着的用height控制线条宽度
16 # 设置字符串到x轴
17 plt.yticks(range(len(x)),x)
18 
19 plt.grid(alpha=0.3)  # 添加网格
20 plt.ylabel(电影名称)
21 plt.xlabel(票房)
22 plt.title(票房前20的电影)
23 
24 plt.show()

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练习二:假设知道了列表a中电影分别在2017-09-14(b_14),2017-09-15(b_15),2017-09-16(b_16)三天的票房,为了展示列表中电影本身的票房以及同其它电影的数据对比情况,应该如何更加直观的呈现数据?

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]
 1 from matplotlib import pyplot as plt
 2 import matplotlib
 3 
 4 font = {family: MicroSoft YaHei}
 5 matplotlib.rc(font, **font)  # 使支持中文
 6 
 7 a = ["猩球崛起3:终极之战","敦刻尔克","蜘蛛侠:英雄归来","战狼2"]
 8 b_16 = [15746,312,4497,319]
 9 b_15 = [12357,156,2045,168]
10 b_14 = [2358,399,2358,362]
11 
12 bar_width = 0.2  # 绘制多个条形图,这里不能大于0.3
13 # 让后两个条形,向后移动一个bar_width
14 x_14 = list(range(len(a)))
15 x_15 = [i+bar_width for i in x_14]
16 x_16 = [i+2*bar_width for i in x_14]
17 
18 plt.figure(figsize=(20, 8), dpi=80)  # 设置图形大小
19 plt.xticks(x_15, a)  # 设置x轴刻度
20 
21 plt.bar(range(len(a)), b_14, width=bar_width, label=9月14日)
22 plt.bar(x_15, b_15, width=bar_width, label=9月15日)
23 plt.bar(x_16, b_16, width=bar_width, label=9月16日)
24 
25 plt.legend()  # 设置图例
26 plt.xlabel(电影名称)
27 plt.ylabel(票房/万)
28 plt.title(对比票房)
29 plt.savefig(./02.png)
30 plt.show()

技术分享图片

 
 

matplotlib库绘制条形图

原文:https://www.cnblogs.com/springionic/p/11150192.html

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