如何将平均 Timedelta 添加到 datetime.time？

Question

我正在尝试估算数据集中缺少的一些 df['Roll_time'] 值。我有 avg_time_diff 变量，它是一个 timedelta64[ns] dtype 和 df['Notif_date']，它是一个 datetime.time。我想为缺少 'Roll_time'.

的每一行计算 avg_time_diff 和 'Notif_date' 的总和

到目前为止我有这个：

avg_time_diff = df['Time_diff'].mean()
df['Time_diff'].fillna(avg_time_diff, inplace=True)

df['Roll_time'].fillna(avg_time_diff + df['Notif_time'])

我在运行代码时遇到此错误：

TypeError: unsupported operand type(s) for +: 'Timedelta' and 'datetime.time'

Answer 1

您还需要将 datetime.time 对象转换为 timedelta 以便算术有效。

例如：

import datetime
import pandas as pd

# some dummy data:
df = pd.DataFrame({'Time_diff': [pd.Timedelta(hours=1), pd.Timedelta(hours=2), pd.NaT, pd.Timedelta(hours=4)],
                   'Notif_time': [datetime.time(1,2,3), datetime.time(2,3,4), datetime.time(4,5,6), datetime.time(7,8,9)]})

# Time_diff column and avg_time_diff are of dtype Timedelta...
avg_time_diff = df['Time_diff'].mean() 
df['Time_diff'] = df['Time_diff'].fillna(avg_time_diff)

# need to cast Notif_time to Timedelta as well so that the arithmetic works out:
df['Roll_time'] = avg_time_diff + pd.to_timedelta(df['Notif_time'].astype(str))

# df['Roll_time']
# 0   0 days 03:22:03
# 1   0 days 04:23:04
# 2   0 days 06:25:06
# 3   0 days 09:28:09
# Name: Roll_time, dtype: timedelta64[ns]

如果您希望输出为 datetime 类型（包含所有格式选项等），您可以通过添加日期来实现：

# to get from timedelta to datetime, you can add the timedelta column to today's date:
df['roll_datetime'] = pd.Timestamp('now').floor('d') + df['Roll_time']

# df['roll_datetime']
# 0   2021-02-04 03:22:03
# 1   2021-02-04 04:23:04
# 2   2021-02-04 06:25:06
# 3   2021-02-04 09:28:09
# Name: roll_datetime, dtype: datetime64[ns]

进一步阅读：Format timedelta to string

如何将平均 Timedelta 添加到 datetime.time？

How do I add an average Timedelta to a datetime.time?

python

datetime

timedelta

pandas