Pandas 计算一组时间戳中的小时数和一个固定数字之间的差值

我有以下数据帧。我试图实现的是，对于每个“工作日期”，“花费的时间”列中的小时数总和应等于7。例如，2019年6月10日，小时数之和已经是7，因此无需调整。2019年6月12日，小时数之和为4.25，因此我需要插入一行，其中包含“Tab_description”差异，该差异将显示为“花费的时间”下的差异2.75。2019年6月13日和2019年6月14日已经达到7，因此无需在那里做任何事情。在2019年6月19日的情况下，我需要执行与2019年6月12日相同的操作，插入一行，总和为6，使总和达到7。谢谢你的帮助

Date_worked Tab_description Time_spent
    0   6/10/2019   Perform planning procedures 7.0
    1   6/11/2019   Perform planning procedures 7.0
    2   6/12/2019   Time off (away from the office) 2.25
    3   6/12/2019   Staff meeting   1.0
    4   6/12/2019   Accounting & Risk Management Luncheon   1.0
    5   6/13/2019   Perform planning procedures 7.0
    6   6/14/2019   Time off (away from the office) 2.0
    7   6/14/2019   Review policies and procedures  5.0
    8   6/17/2019   Time off (away from the office) 7.0
    9   6/18/2019   Perform planning procedures 7.0
    10  6/19/2019   Staff meeting   1.0
    11  6/20/2019   Time off (away from the office) 2.0
    12  6/21/2019   Time off (away from the office) 1.0
    13  6/24/2019   Staff meeting (FY 20 planning)  7.0
    14  6/25/2019   FCR Kick-off meeting    1.0
    15  6/26/2019   Time off (away from the office) 1.5
    16  6/26/2019   Staff meeting   1.0
    17  6/28/2019   Time off (away from the office) 1.0

---

有很多方法可以做到这一点，我将向您展示如何使用

groupby

&

concat

pd.concat(
    [
        df,
        df2.dropna()
        .drop("Time_spent", axis=1)
        .rename(columns={"variance": "Time_spent"}),
    ],
    sort=False,
)
print(df)


  Date_worked                           Tab_description  Time_spent
0    6/10/2019              Perform planning procedures         7.00
1    6/11/2019              Perform planning procedures         7.00
2    6/12/2019          Time off (away from the office)         0.25
3    6/12/2019                          Staff meeting           1.00
4    6/12/2019  Accounting & Risk Management Luncheon           1.00
5    6/13/2019              Perform planning procedures         7.00
6    6/14/2019          Time off (away from the office)         2.00
7    6/14/2019          Review policies and procedures          5.00
8    6/17/2019          Time off (away from the office)         7.00
9    6/18/2019              Perform planning procedures         7.00
10   6/19/2019                          Staff meeting           1.00
11   6/20/2019          Time off (away from the office)         2.00
12   6/21/2019          Time off (away from the office)         1.00
13   6/24/2019                        Staff meeting (FY         7.00
14   6/25/2019                  FCR Kick-off meeting            1.00
15   6/26/2019          Time off (away from the office)         1.50
16   6/26/2019                          Staff meeting           1.00
17   6/28/2019          Time off (away from the office)         1.00
2    6/12/2019                                Difference       -4.75
7    6/19/2019                                Difference       -6.00
8    6/20/2019                                Difference       -5.00
9    6/21/2019                                Difference       -6.00
11   6/25/2019                                Difference       -6.00
12   6/26/2019                                Difference       -4.50
13   6/28/2019                                Difference       -6.00

首先让我们算出总时间和差值

print(df)
      Date_worked                           Tab_description  Time_spent
0    6/10/2019              Perform planning procedures         7.00
1    6/11/2019              Perform planning procedures         7.00
2    6/12/2019          Time off (away from the office)         0.25
3    6/12/2019                          Staff meeting           1.00
4    6/12/2019  Accounting & Risk Management Luncheon           1.00
5    6/13/2019              Perform planning procedures         7.00
6    6/14/2019          Time off (away from the office)         2.00
7    6/14/2019          Review policies and procedures          5.00
8    6/17/2019          Time off (away from the office)         7.00
9    6/18/2019              Perform planning procedures         7.00
10   6/19/2019                          Staff meeting           1.00
11   6/20/2019          Time off (away from the office)         2.00
12   6/21/2019          Time off (away from the office)         1.00
13   6/24/2019                        Staff meeting (FY         7.00
14   6/25/2019                  FCR Kick-off meeting            1.00
15   6/26/2019          Time off (away from the office)         1.50
16   6/26/2019                          Staff meeting           1.00
17   6/28/2019          Time off (away from the office)         1.00

我们从

groupby

和一个简单的差分和开始，将其分配给一个名为df2的新变量

df2 = df.groupby('Date_worked')['Time_spent'].sum().reset_index()
df2['variance'] = df2['Time_spent'] - 7.00

我们现在创建您的选项卡列并创建您要求的描述

df2.loc[df2['variance'] != 0, 'Tab_description'] = 'Difference'

然后，我们删除所有NaN行，删除

'Time\u-spend'

列，并将

concat中的'Variance'列重命名为timespent

pd.concat(
    [
        df,
        df2.dropna()
        .drop("Time_spent", axis=1)
        .rename(columns={"variance": "Time_spent"}),
    ],
    sort=False,
)
print(df)


  Date_worked                           Tab_description  Time_spent
0    6/10/2019              Perform planning procedures         7.00
1    6/11/2019              Perform planning procedures         7.00
2    6/12/2019          Time off (away from the office)         0.25
3    6/12/2019                          Staff meeting           1.00
4    6/12/2019  Accounting & Risk Management Luncheon           1.00
5    6/13/2019              Perform planning procedures         7.00
6    6/14/2019          Time off (away from the office)         2.00
7    6/14/2019          Review policies and procedures          5.00
8    6/17/2019          Time off (away from the office)         7.00
9    6/18/2019              Perform planning procedures         7.00
10   6/19/2019                          Staff meeting           1.00
11   6/20/2019          Time off (away from the office)         2.00
12   6/21/2019          Time off (away from the office)         1.00
13   6/24/2019                        Staff meeting (FY         7.00
14   6/25/2019                  FCR Kick-off meeting            1.00
15   6/26/2019          Time off (away from the office)         1.50
16   6/26/2019                          Staff meeting           1.00
17   6/28/2019          Time off (away from the office)         1.00
2    6/12/2019                                Difference       -4.75
7    6/19/2019                                Difference       -6.00
8    6/20/2019                                Difference       -5.00
9    6/21/2019                                Difference       -6.00
11   6/25/2019                                Difference       -6.00
12   6/26/2019                                Difference       -4.50
13   6/28/2019                                Difference       -6.00

@尽管我很乐意帮忙，但我已经花了很多时间研究工作时间表和劳动数据。如果这个答案足够，请随意打绿色勾，这样问题就可以结束了