爱站程序员基地练习一
为了对某一产品进行合理定价，我们对此类商品进行了试销实验，价格与需求量数据如下。利用图表分析规律。
price = [60,80,40,30,70,90,95]
sales = [100,50,120,135,65,45,40]
代码如下：
import matplotlib.pyplot as pltimport matplotlibfont = {\'family\':\'SimHei\',\'weight\':\'bold\',\'size\':12}matplotlib.rc(\"font\",**font) #全局字体格式设置price = [60,80,40,30,70,90,95]sales = [100,50,120,135,65,45,40]plt.scatter(price,sales) #绘制散点图plt.xlabel(\'价格\')x_t = range(20,100,10)x_l = [f\'{i}元\' for i in x_t]plt.xticks(x_t,x_l) #设置x轴刻度及刻度标签plt.ylabel(\'需求\')y_t = range(30,145,10)y_l = [f\'{i}件\' for i in y_t]plt.yticks(y_t,y_l) #设置y轴刻度及刻度标签#为各点设置注释for x,y in zip(price,sales):plt.annotate(\'({},{})\'.format(x,y),(x,y),(x-5,y+5))plt.title(\'需求与价格关系图\') #设置标题plt.savefig(\'需求与价格关系图.png\') #保存图片plt.show()
绘得图表如下：
从图可以看出，需求量与该商品的价格呈负相关，随着商品价格的提高，需求量呈直线下降趋势。
练习2
电影数据如下：
movies_name = [“变身特工”,“美丽人生”,“鲨海逃生”,“熊出没·狂野大陆”]
day_12 = [2358,399,2358,362]
day_13 = [12357,156,2045,168]
day_14 = [15746,312,4497,319]
需求：
• 直观体现出不同电影近三天的票房的对比情况
代码如下：
import matplotlib.pyplot as pltimport matplotlibfont = {\'family\':\'SimHei\',\'weight\':\'bold\',\'size\':12}matplotlib.rc(\"font\",**font) #设置全局字体格式movies_name = [\"变身特工\",\"美丽人生\",\"鲨海逃生\",\"熊出没·狂野大陆\"]day_12 = [2358,399,2358,362]day_13 = [12357,156,2045,168]day_14 = [15746,312,4497,319]#求得三天的x轴刻度x_t_13 = range(len(movies_name))x_t_12 = [i-0.3 for i in x_t_13]x_t_14 = [i+0.3 for i in x_t_13]#绘制直方图plt.bar(x_t_12,day_12,width=0.3 ,label=\'day_12\')plt.bar(x_t_13,day_13,width=0.3 ,label=\'day_13\')plt.bar(x_t_14,day_14,width=0.3 ,label=\'day_14\')#定义的自动加注释的函数def auto_annotate(x_t,y_t):for x,y in zip(x_t,y_t):plt.annotate(f\'{y}\',(x,y),(x,y+10))auto_annotate(x_t_12,day_12)auto_annotate(x_t_13,day_13)auto_annotate(x_t_14,day_14)plt.legend() #添加图例plt.xticks(x_t_13,movies_name,rotation=45) #设置X轴刻度及刻度标签day = day_12 + day_13 + day_14plt.yticks(range(min(day),max(day)+1000,1000)) #设置y轴刻度plt.title(\'四部电影三日票房\') #添加标题plt.savefig(\'四部电影三日票房.png\') #保存图片plt.show()
生成图表如下：
