概率论 DEMO

import codecsimport csv
import numpy as npimport matplotlib.pyplot as pltimport mathimport pandas as pd

def method(qwl,fcl):    #生成1000个数字    ls =  np.random.rand(1000)    # ls = [1,2,3,4,5,6,7]    # print(ls)    #求平均值    arr_mean = np.mean(ls)    # print(arr_mean)    #期望    qw = 0    for i in ls:        qw +=i*1/len(ls)    # print("期望=",qw)    qwl.append(qw)
    bzx = math.sqrt(1000) * (arr_mean - 0.5)
    fcl.append(bzx)
# def bzc(ls =list,qwl =list,fcl=list):##     for i in qwl:#         fcl.append(np.sqrt(1000)*(np.mean(ls)-i))
def data_write_csv(file_name, datas):#file_name为写入CSV文件的路径，datas为要写入数据列表    file_csv = codecs.open(file_name,'w+','utf-8')#追加    writer = csv.writer(file_csv, delimiter=' ', quotechar=' ', quoting=csv.QUOTE_MINIMAL)    for data in datas:        writer.writerow(data)    print("保存文件成功，处理结束")
if __name__ == '__main__':    qwl =[]    fcl =[]    for i in range(0,5000):        print(i)        method(qwl,fcl)    print(fcl)    print(qwl)    #    # fig1 = plt.figure(2)    # plt.subplot(211)    # plt.plot(qwl)    # plt.title = "期望"    #    # # subplot(211)把绘图区域等分为2行*1列共两个区域，然后在区域1（上区域）中创建一个轴对象    # plt.subplot(212)  # 在区域2（下区域）创建一个轴对象    # plt.plot(fcl)    # plt.title = "标准差"    # plt.show()    data = []    data.append(qwl)    data = np.transpose(data)    data_write_csv("demo1.csv",data)
    # matplotlib模块绘制直方图    # 读入数据    # Titanic = pd.read_csv('/Users/bytedance/Desktop/demo.csv')    #    # # 绘制直方图    # plt.hist(x=Titanic.Age,  # 指定绘图数据    #          bins=20,  # 指定直方图中条块的个数    #          color='steelblue',  # 指定直方图的填充色    #          edgecolor='black'  # 指定直方图的边框色    #          )    # # 添加x轴和y轴标签    # plt.xlabel('年龄')    # plt.ylabel('频数')    # # 添加标题    # plt.title('乘客年龄分布')    # # 显示图形    # plt.show()