TXT文件中数据求均值并保存

import pandas as pd
import json
import numpy as np

 #将pose数据x y label保存到list中
pose = []

def save_to_json(file,output_path):
    jsObj = json.dumps(file)
    fileObject = open(output_path + ‘pose.json‘, ‘w‘)
    fileObject.write(jsObj)
    fileObject.close()

def data_average(value_pose_x):
    sum = 0
    b = len(value_pose_x)
    for i in value_pose_x:
        sum = sum + i
    average = str(sum / b)
    # print(average)
    return average

def pose(filename_pose):

    data_pose = pd.read_table(filename_pose,sep=‘\t‘)  #low_memory=False

    label_pose = data_pose.values[:,0] #[‘nose‘ ‘left eye‘ ‘right eye‘ ... ‘right hip‘ ‘left knee‘ ‘right knee‘]
    # print(label_pose)

    value_cnt = {}  # 将结果用一个字典存储
    for value in label_pose:  # 统计结果
        value_cnt[value] = value_cnt.get(value, 0) + 1   # get(value, num)函数的作用是获取字典中value对应的键值, num=0指示初始值大小。

    tmp_save = {}
    # print(value_cnt.keys()) #17个
    for key in value_cnt.keys():
        if key != "label":
            pose_label = data_pose.loc[data_pose[‘label‘]==key,:]   #DataFrame

            value_pose_x = pose_label.loc[:, ‘x‘]
            value_pose_y = pose_label.loc[:, ‘y‘]
            value_pose_score = pose_label.loc[:, ‘score‘]

            value_pose_x =list(map(int,value_pose_x)) #字符串数组转成int数组
            value_pose_y =list(map(int,value_pose_y)) #字符串数组转成int数组
            value_pose_score =list(map(float,value_pose_score)) #字符串数组转成float数组

            value_x = data_average(value_pose_x) #获取平均值
            value_y = data_average(value_pose_y) #获取平均值
            value_score = data_average(value_pose_score) #获取平均值

            tmp_save.setdefault(key,[]).append(value_x) #保存到字典中
            tmp_save.setdefault(key,[]).append(value_y) #保存到字典中
            tmp_save.setdefault(key,[]).append(value_score) #保存到字典中

    save_to_json(tmp_save,output_path) #保存到本地

if __name__ == ‘__main__‘:
    data_path = r"E:\1Test\pose.txt" #数据存储路径
    output_path = r‘E:\1Test\\‘ #数据输出保存路径
    pose(data_path)