編寫一個 Python 程式,為給定的資料框本地化亞洲時區
假設您有時間序列並且結果會作為本地化亞洲時區顯示,如下所示,
Index is: DatetimeIndex(['2020-01-05 00:30:00+05:30', '2020-01-12 00:30:00+05:30', '2020-01-19 00:30:00+05:30', '2020-01-26 00:30:00+05:30', '2020-02-02 00:30:00+05:30'], dtype='datetime64[ns, Asia/Calcutta]', freq='W-SUN')
解決方案
定義資料框
使用pd.date_range()函式建立時間序列,其中開始時間為‘2020-01-01 00:30’,週期為5,時區為‘Asia/Calcutta’,然後將其儲存為time_index。
time_index = pd.date_range('2020-01-01 00:30', periods = 5, freq ='W',tz = 'Asia/Calcutta')
設定df.index以儲存time_index中本地化的時區
df.index = time_index
最後列印本地化的時區
示例
我們檢視以下程式碼以更好地理解 -
import pandas as pd df = pd.DataFrame({'Id':[1,2,3,4,5], 'City':['Mumbai','Pune','Delhi','Chennai','Kolkata']}) time_index = pd.date_range('2020-01-01 00:30', periods = 5, freq ='W', tz = 'Asia/Calcutta') df.index = time_index print("DataFrame is:\n",df) print("Index is:\n",df.index)
輸出
DataFrame is: Id City 2020-01-05 00:30:00+05:30 1 Mumbai 2020-01-12 00:30:00+05:30 2 Pune 2020-01-19 00:30:00+05:30 3 Delhi 2020-01-26 00:30:00+05:30 4 Chennai 2020-02-02 00:30:00+05:30 5 Kolkata Index is: DatetimeIndex(['2020-01-05 00:30:00+05:30', '2020-01-12 00:30:00+05:30', '2020-01-19 00:30:00+05:30', '2020-01-26 00:30:00+05:30', '2020-02-02 00:30:00+05:30'], dtype='datetime64[ns, Asia/Calcutta]', freq='W-SUN')
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