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Pandas (Python)：如何将值应用于相似的行？

[英]Pandas (Python): How to apply values to similar row?

 原文  2020-01-13 13:42:18  3   3    python/ pandas

问题描述

sorry for the badly phrased question, currently only the first hour is updated with holiday.抱歉措辞不好的问题，目前只有第一个小时更新了假期。

eg例如

  • 2013-01-01 00:00:00 - New Years Day 2013-01-01 00:00:00 - 元旦
  • 2013-01-01 00:00:00 - None 2013-01-01 00:00:00 - 无
  • 2013-01-01 00:00:00 - None 2013-01-01 00:00:00 - 无

I would like to apply similar holidays to the same date using Pandas (Python).我想使用 Pandas (Python) 将类似的假期应用于同一日期。

What would be the most efficient method to apply the holiday to the same dates, there are a number of other holidays to apply as well?将假期应用于相同日期的最有效方法是什么，还有许多其他假期可以申请？

Thank you in advance!先感谢您！

Screenshot of CSV in question有问题的 CSV 的屏幕截图

3 个解决方案

解决方案1
 2  2020-01-13 13:52:12

Using a library called holidays together with pandas apply could be a great solution to your problem.将名为holiday的库与pandas apply 一起使用可能是解决您问题的好方法。 Here is a short contained example example这是一个简短的包含示例示例

import pandas as pd
import holidays

us_holidays = holidays.UnitedStates()

# Create a sample DataFrame. You can just use your own
data = pd.DataFrame(pd.date_range('2020-01-01', '2020-01-30'), columns=['date'])

data['holiday'] = data['date'].apply(lambda x: us_holidays.get(x))
print(data)

Output输出

        date                      holiday
0  2020-01-01               New Year's Day
1  2020-01-02                         None
2  2020-01-03                         None
3  2020-01-04                         None
4  2020-01-05                         None
5  2020-01-06                         None
6  2020-01-07                         None
7  2020-01-08                         None
8  2020-01-09                         None
9  2020-01-10                         None
10 2020-01-11                         None
11 2020-01-12                         None
12 2020-01-13                         None
13 2020-01-14                         None
14 2020-01-15                         None
15 2020-01-16                         None
16 2020-01-17                         None
17 2020-01-18                         None
18 2020-01-19                         None
19 2020-01-20  Martin Luther King, Jr. Day
20 2020-01-21                         None
21 2020-01-22                         None
22 2020-01-23                         None
23 2020-01-24                         None
24 2020-01-25                         None
25 2020-01-26                         None
26 2020-01-27                         None
27 2020-01-28                         None
28 2020-01-29                         None
29 2020-01-30                         None

解决方案2
 1  2020-01-13 13:45:54

You can try using the apply method: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html您可以尝试使用 apply 方法： https : //pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html

The input to this is the function you want to be applied to each row.对此的输入是您要应用于每一行的函数。 And in this case "axis" should be zero so that it is applied to each row.在这种情况下，“轴”应该为零，以便将其应用于每一行。

解决方案3
 1 已采纳  2020-01-13 14:35:28

IIUC, you have only the first hour of a day listed with a holiday. IIUC，你只有一天的第一个小时有假期。 Here is a small sample of a dataframe with two months of data and three holidays on three separate days.这是一个数据框的小样本，其中包含两个月的数据和三个不同天的三个假期。

import pandas as pd
import numpy as np

df = pd.DataFrame({'temp':np.random.randint(50,110, 60*24)}, index=pd.date_range('2013-01-01', periods=(60*24), freq='H'))

df['Holiday'] = np.nan

df.loc['2013-01-01 00:00:00', 'Holiday'] = 'New Years Day'
df.loc['2013-02-02 00:00:00', 'Holiday'] = 'Groundhog Day'
df.loc['2013-02-14 00:00:00', 'Holiday'] = "Valentine's Day"

Now, let's use groupby with day from DatetimeIndex and ffill :现在，让我们使用groupby有day从DatetimeIndex和ffill ：

df['Holiday'] = df.groupby(df.index.day)['Holiday'].ffill()

Let's look at a few records:我们来看几条记录：

print(df.head(40))
print(df['2013-02-02'])
print(df['2013-02-13':'2013-02-15'])

Output:输出：

                     temp        Holiday
2013-01-01 00:00:00    51  New Years Day
2013-01-01 01:00:00    71  New Years Day
2013-01-01 02:00:00    61  New Years Day
2013-01-01 03:00:00    90  New Years Day
2013-01-01 04:00:00    77  New Years Day
2013-01-01 05:00:00    69  New Years Day
2013-01-01 06:00:00    50  New Years Day
2013-01-01 07:00:00    99  New Years Day
2013-01-01 08:00:00    86  New Years Day
2013-01-01 09:00:00    72  New Years Day
2013-01-01 10:00:00    89  New Years Day
2013-01-01 11:00:00    62  New Years Day
2013-01-01 12:00:00    53  New Years Day
2013-01-01 13:00:00    91  New Years Day
2013-01-01 14:00:00    51  New Years Day
2013-01-01 15:00:00    93  New Years Day
2013-01-01 16:00:00    97  New Years Day
2013-01-01 17:00:00    83  New Years Day
2013-01-01 18:00:00    87  New Years Day
2013-01-01 19:00:00    58  New Years Day
2013-01-01 20:00:00    84  New Years Day
2013-01-01 21:00:00    92  New Years Day
2013-01-01 22:00:00   106  New Years Day
2013-01-01 23:00:00   104  New Years Day
2013-01-02 00:00:00    78            NaN
2013-01-02 01:00:00   104            NaN
2013-01-02 02:00:00    96            NaN
2013-01-02 03:00:00   103            NaN
2013-01-02 04:00:00    60            NaN
2013-01-02 05:00:00    87            NaN
2013-01-02 06:00:00   108            NaN
2013-01-02 07:00:00    85            NaN
2013-01-02 08:00:00    67            NaN
2013-01-02 09:00:00    61            NaN
2013-01-02 10:00:00    91            NaN
2013-01-02 11:00:00    79            NaN
2013-01-02 12:00:00    99            NaN
2013-01-02 13:00:00    82            NaN
2013-01-02 14:00:00    75            NaN
2013-01-02 15:00:00    90            NaN
                     temp        Holiday
2013-02-02 00:00:00    82  Groundhog Day
2013-02-02 01:00:00    58  Groundhog Day
2013-02-02 02:00:00   102  Groundhog Day
2013-02-02 03:00:00    90  Groundhog Day
2013-02-02 04:00:00    79  Groundhog Day
2013-02-02 05:00:00    50  Groundhog Day
2013-02-02 06:00:00    50  Groundhog Day
2013-02-02 07:00:00    83  Groundhog Day
2013-02-02 08:00:00    80  Groundhog Day
2013-02-02 09:00:00    50  Groundhog Day
2013-02-02 10:00:00    52  Groundhog Day
2013-02-02 11:00:00    69  Groundhog Day
2013-02-02 12:00:00   100  Groundhog Day
2013-02-02 13:00:00    61  Groundhog Day
2013-02-02 14:00:00    62  Groundhog Day
2013-02-02 15:00:00    76  Groundhog Day
2013-02-02 16:00:00    83  Groundhog Day
2013-02-02 17:00:00   109  Groundhog Day
2013-02-02 18:00:00   109  Groundhog Day
2013-02-02 19:00:00    81  Groundhog Day
2013-02-02 20:00:00    52  Groundhog Day
2013-02-02 21:00:00   108  Groundhog Day
2013-02-02 22:00:00    68  Groundhog Day
2013-02-02 23:00:00    75  Groundhog Day
                     temp          Holiday
2013-02-13 00:00:00    93              NaN
2013-02-13 01:00:00    93              NaN
2013-02-13 02:00:00    74              NaN
2013-02-13 03:00:00    97              NaN
2013-02-13 04:00:00    58              NaN
2013-02-13 05:00:00   103              NaN
2013-02-13 06:00:00    79              NaN
2013-02-13 07:00:00    65              NaN
2013-02-13 08:00:00    72              NaN
2013-02-13 09:00:00   100              NaN
2013-02-13 10:00:00    66              NaN
2013-02-13 11:00:00    60              NaN
2013-02-13 12:00:00    95              NaN
2013-02-13 13:00:00    51              NaN
2013-02-13 14:00:00    71              NaN
2013-02-13 15:00:00    58              NaN
2013-02-13 16:00:00    58              NaN
2013-02-13 17:00:00    98              NaN
2013-02-13 18:00:00    61              NaN
2013-02-13 19:00:00    63              NaN
2013-02-13 20:00:00    57              NaN
2013-02-13 21:00:00   102              NaN
2013-02-13 22:00:00    69              NaN
2013-02-13 23:00:00    86              NaN
2013-02-14 00:00:00    94  Valentine's Day
2013-02-14 01:00:00    64  Valentine's Day
2013-02-14 02:00:00    62  Valentine's Day
2013-02-14 03:00:00    59  Valentine's Day
2013-02-14 04:00:00    93  Valentine's Day
2013-02-14 05:00:00    99  Valentine's Day
2013-02-14 06:00:00    64  Valentine's Day
2013-02-14 07:00:00    80  Valentine's Day
2013-02-14 08:00:00    89  Valentine's Day
2013-02-14 09:00:00    96  Valentine's Day
2013-02-14 10:00:00    60  Valentine's Day
2013-02-14 11:00:00    76  Valentine's Day
2013-02-14 12:00:00    82  Valentine's Day
2013-02-14 13:00:00    65  Valentine's Day
2013-02-14 14:00:00    90  Valentine's Day
2013-02-14 15:00:00    62  Valentine's Day
2013-02-14 16:00:00    64  Valentine's Day
2013-02-14 17:00:00    98  Valentine's Day
2013-02-14 18:00:00    52  Valentine's Day
2013-02-14 19:00:00    72  Valentine's Day
2013-02-14 20:00:00   108  Valentine's Day
2013-02-14 21:00:00    85  Valentine's Day
2013-02-14 22:00:00    87  Valentine's Day
2013-02-14 23:00:00    62  Valentine's Day
2013-02-15 00:00:00   106              NaN
2013-02-15 01:00:00    82              NaN
2013-02-15 02:00:00    77              NaN
2013-02-15 03:00:00    52              NaN
2013-02-15 04:00:00    94              NaN
2013-02-15 05:00:00    71              NaN
2013-02-15 06:00:00    95              NaN
2013-02-15 07:00:00    96              NaN
2013-02-15 08:00:00    71              NaN
2013-02-15 09:00:00    69              NaN
2013-02-15 10:00:00    85              NaN
2013-02-15 11:00:00    92              NaN
2013-02-15 12:00:00   106              NaN
2013-02-15 13:00:00    77              NaN
2013-02-15 14:00:00    65              NaN
2013-02-15 15:00:00   104              NaN
2013-02-15 16:00:00    98              NaN
2013-02-15 17:00:00   107              NaN
2013-02-15 18:00:00   106              NaN
2013-02-15 19:00:00    67              NaN
2013-02-15 20:00:00    59              NaN
2013-02-15 21:00:00    81              NaN
2013-02-15 22:00:00    56              NaN
2013-02-15 23:00:00    75              NaN

Note: In this dataframe your datetime column is in the index.注意：在此数据框中，您的日期时间列位于索引中。

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