模拟collections容器解析数据

2021-01-19 15:59:23 阅读：139 来源： 互联网

标签：容器 name data app list waitTime collections 解析 com

# -*- coding:utf-8 -*-
import re
import pandas as pd
import numpy as np


package_dict = {
    "com.tencent.mobileqq":"QQ",
    "com.ss.android.ugc.aweme":"抖音",
    "com.qiyi.video":"爱奇艺",
    "com.smile.gifmaker":"快手",
    "tv.danmaku.bili":"哔哩哔哩",
    "com.UCMobile":"UC浏览器",
    "com.autonavi.minimap":"高德地图",
    "com.tencent.mtt":"QQ浏览器",
    "com.tencent.karaoke":"全民k歌",
    "com.ss.android.article.video":"西瓜视频",
    "com.ss.android.article.news":"今日头条",
    "com.sina.weibo":"微博",
    "com.jingdong.app.mall":"京东",
    "com.youku.phone":"优酷",
    "com.suning.mobile.ebuy":"苏宁易购",
    "com.ximalaya.ting.android":"喜马拉雅",
    "com.dianping.v1":"大众点评",
    "com.tencent.qqmusic":"QQ音乐"
}
list_aveTime = []
package_count = dict()
with open("./appStartTimeAm.csv","r") as f:
    for lines in f.readlines():
        line = lines.strip()
        # print(line)
        app_list = line.split(',',6)
        # print(app_list[6])
        app_name = app_list[0].split('/',1)[0]
        waitTime = app_list[4]
        if app_list[6] != "TRUE":
            continue
        app_waitTime = (app_name + ':'+ waitTime).split(':')
        # print(app_waitTime)
        name = app_waitTime[0]
        time = app_waitTime[1]
        if name not in package_count:
            package_count[name] = list()
        package_count[name].append(int(time))

    for key, val in package_count.items():
        name = package_dict[key]
        ave_time =np.mean(val)
        print(name,ave_time)
        list_aveTime.append([name,ave_time]+val)
         # ,columns=['name','ave_time','第1次','第2次','第3次','第4次','第5次','第6次',
         #                                    '第7次','第8次','第9次','第10次']
    df = pd.DataFrame(list_aveTime)
    df.to_excel('waitTime解析结果.xlsx',index=False)

from collections import defaultdict
import pandas as pd

all_data = defaultdict(list)
data = pd.read_csv(r'./appStartTimeAm.csv')
app_name = data['appName']
waitTime = data['waitTime']
ColdStart = data['isNewColdStart']
for Name, wait,cold_start in zip(app_name,waitTime,ColdStart):
    
    print(Name,wait,type(cold_start))
    for i in data['appName'].unique():
        if Name == i and cold_start:
            all_data[Name].append(wait)
        else:
            if isinstance(type(cold_start),float):
                continue

df = pd.DataFrame.from_dict(all_data, orient='index')
df.to_excel("waitTime解析表.xlsx")

标签：容器,name,data,app,list,waitTime,collections,解析,com
来源： https://blog.csdn.net/weixin_38185649/article/details/112843220

本站声明： 1. iCode9 技术分享网（下文简称本站）提供的所有内容，仅供技术学习、探讨和分享；
2. 关于本站的所有留言、评论、转载及引用，纯属内容发起人的个人观点，与本站观点和立场无关；
3. 关于本站的所有言论和文字，纯属内容发起人的个人观点，与本站观点和立场无关；
4. 本站文章均是网友提供，不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属；如您发现该文章侵犯了您的权益，可联系我们第一时间进行删除；
5. 本站为非盈利性的个人网站，所有内容不会用来进行牟利，也不会利用任何形式的广告来间接获益，纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。

ICode9

模拟collections容器解析数据