如何從 Pandas 的日期時間列中提取月份和年份

Suraj Joshi 2023年1月30日
  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
如何從 Pandas 的日期時間列中提取月份和年份

我們可以分別使用 pandas.Series.dt.year()pandas.Series.dt.month() 方法從 Datetime 列中提取年份和月份。如果資料不是 Datetime 型別,則需要先將其轉換為 Datetime。我們還可以使用 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

應用於 Datetime 型別的 pandas.Series.dt.year()pandas.Series.dt.month() 方法分別返回系列物件中 Datetime 條目的年和月的 numpy 陣列。

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)

輸出:

        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,如果該列不是 Datetime 型別,則應首先使用 to_datetime() 方法將該列轉換為 Datetime 型別。

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)

輸出:

        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,將格式程式碼作為輸入,並返回表示輸出中指定的特定格式的字串。我們使用%Y%m 作為格式程式碼來提取年份和月份。

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)

輸出:

        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種簡單方法是檢索 pandas.DatetimeIndex 物件的年份和月份屬性的值類。

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)

輸出:

        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 類是 datetime64 資料型別的不變型別 ndarray。它具有年,月,天等屬性。

作者: Suraj Joshi
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Suraj Joshi is a backend software engineer at Matrice.ai.

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