Question

假设我有这个数据框。

import pandas as pd
data = {"Date": ["2018-08-05", "2018-08-05", "2018-08-05", "2018-08-05", "2018-08-06"],  
        "Time_End":["2018-08-05 13:50:00", "2018-08-05 14:26:00", "2018-08-05 17:30:00", "2018-08-05 17:10:00", "2018-08-06 11:23:00"],
        "Reason":["blah1", "blah2", "blah3", "blah4", "blah5"]
       }
df = pd.DataFrame.from_dict(data)
df

        Date             Time_End          Reason
0   2018-08-05      2018-08-05 13:50:00     blah1
1   2018-08-05      2018-08-05 14:26:00     blah2
2   2018-08-05      2018-08-05 17:30:00     blah3
3   2018-08-05      2018-08-05 17:10:00     blah4
4   2018-08-06      2018-08-06 11:23:00     blah5

我只想将“ Time_End”中的日期提取到名为“ Birth_date”的新列中。但是，我也想检查时间是否过了17:00。如果是这样，提取的日期将加一成为第二天。下面显示了所需的输出。

    Date        Birth_date      Time_End            Reason
0   2018-08-05  2018-08-05  2018-08-05 13:50:00     blah1
1   2018-08-05  2018-08-05  2018-08-05 14:26:00     blah2
2   2018-08-05  2018-08-06  2018-08-05 17:30:00     blah3
3   2018-08-05  2018-08-06  2018-08-05 17:10:00     blah4
4   2018-08-06  2018-08-06  2018-08-06 11:23:00     blah5

我想到了这一点，但它并没有达到我的预期。

df["after_17"] = df["Time_End"].dt.hour > 17
df["birth_date"] = df["after_17"].map(lambda x: df["Time_End"].dt.date if x  else df["Time_End"].dt.date + pd.DateOffset(1))

它将输出连接在一起，并形成一行。我如何使其正常工作？我也欢迎其他解决方案。

Answer 1

使用timedelta库中的datetime方法向Time_End添加7小时，然后使用dt.date仅提取日期部分。

import pandas as pd
from datetime import timedelta

data = {"Date": ["2018-08-05", "2018-08-05", "2018-08-05", "2018-08-05", "2018-08-06"],  
        "Time_End":["2018-08-05 13:50:00", "2018-08-05 14:26:00", "2018-08-05 17:30:00", "2018-08-05 17:10:00", "2018-08-06 11:23:00"],
        "Reason":["blah1", "blah2", "blah3", "blah4", "blah5"]
       }

df = pd.DataFrame.from_dict(data).astype({'Time_End': 'datetime64'})

td = timedelta(hours=7)

df['Birth_Date'] = (df.Time_End + td).dt.date

输出

    Date        Time_End            Reason  Birth_Date
0   2018-08-05  2018-08-05 13:50:00 blah1   2018-08-05
1   2018-08-05  2018-08-05 14:26:00 blah2   2018-08-05
2   2018-08-05  2018-08-05 17:30:00 blah3   2018-08-06
3   2018-08-05  2018-08-05 17:10:00 blah4   2018-08-06
4   2018-08-06  2018-08-06 11:23:00 blah5   2018-08-06

Answer 2

首先创建1天的DateOffset：

date_offset = pd.tseries.offsets.DateOffset(n=1)
df['Birth_date'] = df.Time_End.apply(lambda x: x + date_offset if x.hour >= 17 else x).dt.date

Answer 3

您需要：

import numpy as np
import datetime as dt
import pandas as pd
data = {"Date": ["2018-08-05", "2018-08-05", "2018-08-05", "2018-08-05", "2018-08-06"],  
        "Time_End":["2018-08-05 13:50:00", "2018-08-05 14:26:00", "2018-08-05 17:30:00", "2018-08-05 17:10:00", "2018-08-06 11:23:00"],
        "Reason":["blah1", "blah2", "blah3", "blah4", "blah5"]
       }
df = pd.DataFrame(data)

# Convert column into pandas datetime format
df['Time_End'] = pd.to_datetime(df["Time_End"])

# Create a threshold value to compare
t = pd.to_datetime('17:00:00').time()

# Use datetime.timedelta to add a day for condition 
df['Birth_date'] = np.where(df['Time_End'].dt.time < t, df['Time_End'], df["Time_End"] + dt.timedelta(days=1) )

输出：

         Date            Time_End Reason           birthdate
0  2018-08-05 2018-08-05 13:50:00  blah1 2018-08-05 13:50:00
1  2018-08-05 2018-08-05 14:26:00  blah2 2018-08-05 14:26:00
2  2018-08-05 2018-08-05 17:30:00  blah3 2018-08-06 17:30:00
3  2018-08-05 2018-08-05 17:10:00  blah4 2018-08-06 17:10:00
4  2018-08-06 2018-08-06 11:23:00  blah5 2018-08-06 11:23:00

Answer 4

您可以先拆分列，然后再进行比较以添加到日期：

df[['Birth-date', 'Time']] = df['Time_End'].str.split(' ', n=1, expand=True)

熊猫-从日期时间中提取日期，如果时间超过某个小时，则提取一天

4 个答案: