1. 散点图
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假设通过爬虫你获取到了北京2016年3,10月份每天白天的最高气温(分别位于列表a,b),那么此时如何寻找出气温和随时间(天)变化的某种规律?
数据如下所示:
a = [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]
b = [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]
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\Windows\Fonts\msyh.ttc")
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)
fig = plt.figure(figsize=(20,8),dpi=80)
plt.scatter(x_3, y_3, label="3月")
plt.scatter(x_10, y_10, label = "10月")
# 调整x轴的刻度
_x = list(x_3) + list(x_10)
_xtick_labels = ["3月{}号".format(i) for i in x_3]
_xtick_labels += ["3月{}号".format(i) for i in x_3]
plt.xticks(_x[::3], _xtick_labels[::3], fontproperties = my_font, rotation = 45)
# 添加图例
plt.legend(prop = my_font, loc = "best")
# 添加描述信息
plt.xlabel("时间", fontproperties = my_font)
plt.ylabel("温度", fontproperties = my_font)
plt.title("3月份和10月份的气温变化", fontproperties = my_font)
plt.show()
结果展示:
2. 条形图
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] 单位:亿
代码如下所示:
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\Windows\Fonts\msyh.ttc")
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",]
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]
fig = plt.figure(figsize=(20,8), dpi=80)
# 画条形图
plt.bar(x,y,width = 0.4, color = "orange")
# 调整x轴的刻度
plt.xticks(range(len(x)), x, fontproperties = my_font, rotation=90)
plt.show()
绘图结果展示:
- 问题:
- 从图中可以看出,对于电影名长的,展示的并不是太好
- 考虑把电影名换到y轴上,即画横着的条形图
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\Windows\Fonts\msyh.ttc")
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",]
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]
fig = plt.figure(figsize=(20,8), dpi=80)
plt.barh(x,y,height = 0.4, color = "orange")
plt.yticks(range(len(x)), x, fontproperties = my_font)
plt.show()
绘图结果:
- 注意:
- 横着的条形图使用的语法为:plt.barh()
- barh中的参数为bottom,width, height。bottom对应x轴,withth对应y轴,height为条形图的宽度。
假设你知道了列表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他电影的数据对比情况,应该如何更加直观的呈现该数据?
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]
代码如下:
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\Windows\Fonts\msyh.ttc")
x = ["猩球崛起3:终极之战","敦刻尔克","蜘蛛侠:英雄归来","战狼2"]
y_16 = [15746,312,4497,319]
y_15 = [12357,156,2045,168]
y_14 = [2358,399,2358,362]
fig = plt.figure(figsize=(20,8), dpi=80)
bar_width = 0.2
x_14 = list(range(len(x)))
x_15 = [i+bar_width for i in x_14]
x_16 = [i+bar_width*2 for i in x_14]
plt.bar(x_14,y_14, width = bar_width, label = "9月14号")
plt.bar(x_15,y_15, width = bar_width, label = "9月15号")
plt.bar(x_16,y_16, width = bar_width, label = "9月16号")
plt.xticks(x_15, x, fontproperties = my_font)
plt.legend(prop = my_font,loc="best")
plt.show()
绘制结果:
- 注意:
- 在一个图中画多个条形图做对比,后面的条形图的x轴要往右边移动一个柱状的宽度,否则画出的图形会重合。
3. 直方图
假设你获取了250部电影的时长(列表a中),希望统计出这些电影时长的分布状态(比如时长为100分钟到120分钟电影的数量,出现的频率)等信息,你应该如何呈现这些数据?
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]
代码如下:
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:\Windows\Fonts\msyh.ttc")
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]
# 设置组距为3
d = 3
# 组数
num_bins = (max(a)-min(a))//d
fig = plt.figure(figsize=(20,8), dpi=80)
plt.hist(a, num_bins)
plt.xticks(list(range(min(a),max(a)+d,d)))
plt.grid()
plt.show()
绘图结果:
- 注意:
- 画直方图的语法:plt.hist(数据,组数)
- 把数据分为多少组进行统计?
- 组数要适当,太少会有较大的统计误差,太多规律不明显
- 当数据在100个以内时,按数据的多少常分为5-12组。
- 组距:指的是每两个端点的距离。
- 组数=极差/组距