Python Pandas - 如何对具有微秒频率的 DateTimeIndex 进行舍入


要对具有微秒频率的 DateTimeIndex 进行舍入,请使用 DateTimeIndex.round() 方法。对于微秒频率,请将 freq 参数与值 ‘us’ 结合使用。

首先,导入所需的库 −

import pandas as pd

使用周期为 5 且频率为 s(即秒)创建时间序列索引 −

datetimeindex = pd.date_range('2021-09-29 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='28s')

对日期 DateTimeIndex 使用舍入运算,并使用微秒频率。对于微秒频率,我们使用 'us' −

print("\nPerforming round operation with microseconds frequency...\n",
datetimeindex.round(freq='us'))

示例

以下是如何编码 −

import pandas as pd

# DatetimeIndex with period 5 and frequency as s i.e. seconds
# timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-09-29 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='28s')

# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)

# display DateTimeIndex frequency
print("DateTimeIndex frequency...\n", datetimeindex.freq)

# Round operation on DateTimeIndex date with microseconds frequency
# For microseconds frequency, we have used 'us'
print("\nPerforming round operation with microseconds frequency...\n",
datetimeindex.round(freq='us'))

输出

这会生成以下代码 −

DateTimeIndex...
DatetimeIndex(['2021-09-29 07:20:32.261811624+09:30',
'2021-09-29 07:21:00.261811624+09:30',
'2021-09-29 07:21:28.261811624+09:30',
'2021-09-29 07:21:56.261811624+09:30',
'2021-09-29 07:22:24.261811624+09:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='28S')
DateTimeIndex frequency...
<28 * Seconds>

Performing round operation with microseconds frequency...
DatetimeIndex(['2021-09-29 07:20:32.261812+09:30',
'2021-09-29 07:21:00.261812+09:30',
'2021-09-29 07:21:28.261812+09:30',
'2021-09-29 07:21:56.261812+09:30',
'2021-09-29 07:22:24.261812+09:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq=None)

更新于: 2021-10-19

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