Python 按天计算的平均登录时间-分钟

我试图确定平均登录天数和标准偏差天数。我正在为此使用python和pandas包。谢谢你的帮助

数据：

预期产出：

Sun: 13:49:03
Mon: 13:49:02
Tue: 13:49:02

Sun STD: 00:00:01 
Mon STD: 00:00:02
Tue STD: 00:00:05  

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请提供更多数据和/或更详细的说明。到目前为止，解释的马赫数空间太大

我知道您希望看到以下内容（首先复制数据）：

例如，这将为您提供差异

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否则，如果您有更多数据，这将崩溃。请看一下

我可以这样做：

import datetime
import statistics
data_org = ['2016-01-01 13:49:01', '2016-01-02 13:49:03', '2016-01-03 13:49:04', '2016-01-01 13:49:05',
        '2016-01-02 13:49:02', '2016-01-03 14:49:01']

data_dict = {}
for entry in data_org:
    day, time = entry.split(' ')

    time = time.split(':')
    time_secs = datetime.timedelta(hours=int(time[0]), minutes=int(time[1]), seconds=int(time[2])).total_seconds()

    if day in data_dict:
        data_dict[day].append(time_secs)
    else:
        data_dict[day] = [time_secs]

stats = {}
for key, times in data_dict.items():
    stats[key] = [statistics.mean(times), statistics.stdev(times)]

print(data_dict)
print(stats)

然后，您可以重新格式化输出，并根据需要执行所有后期处理。有关转换时间戳的详细信息，请参阅文档

df = pd.DataFrame()
df['A'] = pd.to_datetime(pd.read_clipboard(header=None)[0])
df['B'] = pd.to_datetime(pd.read_clipboard(header=None)[1])

gb = df.B.groupby(df.A.dt.weekday_name)

print(gb.aggregate({'B':max}) - gb.aggregate({'B':min})) 

import datetime
import statistics
data_org = ['2016-01-01 13:49:01', '2016-01-02 13:49:03', '2016-01-03 13:49:04', '2016-01-01 13:49:05',
        '2016-01-02 13:49:02', '2016-01-03 14:49:01']

data_dict = {}
for entry in data_org:
    day, time = entry.split(' ')

    time = time.split(':')
    time_secs = datetime.timedelta(hours=int(time[0]), minutes=int(time[1]), seconds=int(time[2])).total_seconds()

    if day in data_dict:
        data_dict[day].append(time_secs)
    else:
        data_dict[day] = [time_secs]

stats = {}
for key, times in data_dict.items():
    stats[key] = [statistics.mean(times), statistics.stdev(times)]

print(data_dict)
print(stats)