如何从 Pandas 的日期时间列中提取月份和年份

  1. pandas.Series.dt.year()pandas.Series.dt.month() 方法提取月份和年份
  2. strftime() 方法提取年份和月份
  3. pandas.DatetimeIndex.monthpandas.DatetimeIndex.year 提取年份和月份

我们可以分别使用 pandas.Series.dt.year()pandas.Series.dt.month() 方法从 Datetime 列中提取年份和月份。如果数据不是 Datetime 类型,则需要先将其转换为 Datetime。我们还可以使用 pandas.DatetimeIndex.monthpandas.DatetimeIndex.yearstrftime() 方法提取年份和月份。

pandas.Series.dt.year()pandas.Series.dt.month() 方法提取月份和年份

应用于 Datetime 类型的 pandas.Series.dt.year()pandas.Series.dt.month() 方法分别返回系列对象中 Datetime 条目的年和月的 numpy 数组。

import pandas as pd
import numpy as np
import datetime

list_of_dates = ['2019-11-20', '2020-01-02', '2020-02-05','2020-03-10','2020-04-16']
employees=['Hisila', 'Shristi','Zeppy','Alina','Jerry']
df = pd.DataFrame({'Joined date': pd.to_datetime(list_of_dates)},index=employees)

df['Year'] = df['Joined date'].dt.year 
df['Month'] = df['Joined date'].dt.month 
print(df)

输出:

        Joined date  Year  Month
Hisila   2019-11-20  2019     11
Shristi  2020-01-02  2020      1
Zeppy    2020-02-05  2020      2
Alina    2020-03-10  2020      3
Jerry    2020-04-16  2020      4

但是,如果该列不是 Datetime 类型,则应首先使用 to_datetime() 方法将该列转换为 Datetime 类型。

import pandas as pd
import numpy as np
import datetime

list_of_dates = ['11/20/2019', '01/02/2020', '02/05/2020','03/10/2020','04/16/2020']
employees=['Hisila', 'Shristi','Zeppy','Alina','Jerry']
df = pd.DataFrame({'Joined date': pd.to_datetime(list_of_dates)},index=employees)
df['Joined date']= pd.to_datetime(df['Joined date']) 

df['Year'] = df['Joined date'].dt.year 
df['Month'] = df['Joined date'].dt.month 
print(df)

输出:

        Joined date  Year  Month
Hisila   2019-11-20  2019     11
Shristi  2020-01-02  2020      1
Zeppy    2020-02-05  2020      2
Alina    2020-03-10  2020      3
Jerry    2020-04-16  2020      4

strftime() 方法提取年份和月份

strftime() 方法使用 Datetime,将格式代码作为输入,并返回表示输出中指定的特定格式的字符串。我们使用%Y%m 作为格式代码来提取年份和月份。

import pandas as pd
import numpy as np
import datetime

list_of_dates = ['2019-11-20', '2020-01-02', '2020-02-05','2020-03-10','2020-04-16']
employees=['Hisila', 'Shristi','Zeppy','Alina','Jerry']
df = pd.DataFrame({'Joined date': pd.to_datetime(list_of_dates)},index=employees)

df['year'] = df['Joined date'].dt.strftime('%Y')
df['month'] = df['Joined date'].dt.strftime('%m')

print(df)

输出:

        Joined date  year month
Hisila   2019-11-20  2019    11
Shristi  2020-01-02  2020    01
Zeppy    2020-02-05  2020    02
Alina    2020-03-10  2020    03
Jerry    2020-04-16  2020    04

pandas.DatetimeIndex.monthpandas.DatetimeIndex.year 提取年份和月份

Datetime 列中提取月份和年份的另一种简单方法是检索 pandas.DatetimeIndex 对象的年份和月份属性的值类。

import pandas as pd
import numpy as np
import datetime

list_of_dates = ['2019-11-20', '2020-01-02', '2020-02-05','2020-03-10','2020-04-16']
employees=['Hisila', 'Shristi','Zeppy','Alina','Jerry']
df = pd.DataFrame({'Joined date': pd.to_datetime(list_of_dates)},index=employees)

df['year'] = pd.DatetimeIndex(df['Joined date']).year
df['month'] = pd.DatetimeIndex(df['Joined date']).month

print(df)

输出:

        Joined date  Year  Month
Hisila   2019-11-20  2019     11
Shristi  2020-01-02  2020      1
Zeppy    2020-02-05  2020      2
Alina    2020-03-10  2020      3
Jerry    2020-04-16  2020      4

pandas.DatetimeIndex 类是 datetime64 数据类型的不变类型 ndarray。它具有年,月,天等属性。

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