|
#成绩分析及可视化实例import numpy as npimport matplotlibimport matplotlib.pyplot as pltmatplotlib.rcParams['font.family'] = 'SimHei'stuScore = np.loadtxt('student_score.csv',delimiter = ',')#读入成绩文件,返回数组sumEach = np.sum(stuScore[:,1:],axis = 1)#返回每个学生3门课程总分avgEach = np.average(stuScore[:,1:],axis = 0)#返回每个学生每门课程平均分#返回最高分和最低分maxMath = np.max(stuScore[:,1])maxEng = np.max(stuScore[:,2])maxPython = np.max(stuScore[:,3])minMath = np.min(stuScore[:,1])minEng = np.min(stuScore[:,2])minPython = np.min(stuScore[:,3])print(avgEach)print("个人总分情况是：")print(sumEach)print("个人平均分情况是：")print(avgEach)print("班级每门课程最高分：")print(maxMath,maxEng,maxPython)print("班级每门课程最低分：")print(minMath,minEng,minPython)#取出各科成绩mathScore = stuScore[:,1]engScore = stuScore[:,2]pythonScore = stuScore[:,3] bar = plt.subplot(1,2,1)x=['高数','英语','python']plt.bar(x,avgEach)plt.yticks([10,20,30,40,50,60,70,80,90,100]) #设置y轴刻度#plt.show() ##a=0b=0c=0d=0e=0list1=[]for row in stuScore: list1.append(row[3]) if(row[3] |