Python数据分析 2.Matplotlib绘图—常用统计图

1.绘制散点图

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.ttf")y_3 = [6, 20, 7, 13, 8, 14, 6, 17, 6, 7, 9, 8, 20, 19, 17, 13, 17, 10, 12, 12]
y_10 = [25, 26, 30, 26, 13, 27, 15, 22, 23, 28, 20, 22, 28, 12, 21, 29, 14, 21, 15, 26]x_3 = range(1,21)
x_10 = range(31,51)plt.figure(figsize=(20,8),dpi=80)# 使用scatter绘制散点图
plt.scatter(x_3, y_3, label="3月份")
plt.scatter(x_10, y_10, label="10月份")_x = list(x_3)+list(x_10)
_xtick_labels = ["3月{}日".format(i) for i in range(1,21)]
_xtick_labels += ["10月{}日".format(i) for i in range(1,21)]
plt.xticks(_x[::2], _xtick_labels[::2], fontproperties = my_font, rotation = 45)plt.xlabel("时间", fontproperties = my_font)
plt.xlabel("温度", fontproperties = my_font)
plt.title("3月与10月温度比较", fontproperties = my_font, size = 20)plt.legend(loc="upper left", prop=my_font)

2.绘制条形图

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.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：\n最后的骑士","摔跤吧！爸爸","加勒比海盗5：\n死无对证","金刚：骷髅岛","极限特工：\n终极回归","生化危机6：\n终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：\n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] plt.figure(figsize=(20,15),dpi=80)
plt.bar(range(len(a)),b,width=0.3)plt.xticks(range(len(a)),a,fontproperties = my_font,rotation = 90)

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.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] plt.figure(figsize=(20,15),dpi=80)
plt.barh(range(len(a)),b,height=0.3,color="orange")plt.grid(alpha=0.3)
plt.yticks(range(len(a)),a,fontproperties = my_font)

3.绘制多次条形图

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.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]# 设置bar_width来绘制多条形图
bar_width = 0.2x_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]plt.figure(figsize=(20,8),dpi=80)plt.bar(x_14,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")plt.xticks(x_15,a,fontproperties=my_font)plt.legend(prop=my_font)

4.绘制直方图

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.ttf")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 + 1plt.figure(figsize=(20,8),dpi=80)
plt.hist(a,num_bins,density=True)# 设置x轴刻度
plt.xticks(range(min(a),max(a)+d,d))
plt.grid()

条形图方式绘制直方图：

from matplotlib import pyplot as plt
from matplotlib import font_managermy_font = font_manager.FontProperties(fname = "C:/Windows/Fonts/simhei.ttf")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(12),quantity,width=1)# 设置x轴刻度
_x = [i-0.5 for i in range(13)]
_xtick_labels = interval+[150]
plt.xticks(_x, _xtick_labels)plt.grid()

注：未经过统计的数据适合绘制直方图

5.总结

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

使用流程：（1）明确问题（2）选择图形的呈现方式（3）准备数据（4）绘图和图形完善

其他绘图工具：前端框架-ECHARTS，可视化中的github-Plotly

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Python数据分析 2.Matplotlib绘图—常用统计图

Python数据分析 2.Matplotlib绘图—常用统计图

1.绘制散点图

2.绘制条形图

3.绘制多次条形图

4.绘制直方图

5.总结

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