用Python编写程序以针对给定的数据框本地化亚洲时区
假设您有一个时间序列，并将亚洲时区本地化的结果为
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')解决方案
定义一个数据框
使用开始时间为'2020-01-0100:30'，周期=5且tz='Asia/Calcutta'的函数创建时间序列，然后将其存储为time_index。pd.date_range()
time_index = pd.date_range('2020-01-01 00:30', periods = 5, freq ='W',tz = 'Asia/Calcutta')设置df.index为存储来自time_index的本地化时区
df.index = time_index
最后打印本地化的时区
例子
让我们检查以下代码以获得更好的理解-
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)输出
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')