Python Pandas - 如何对频率为毫秒的 TimeDeltaIndex 进行舍入


要对频率为毫秒的 TimeDeltaIndex 进行舍入,请使用 TimeDeltaIndex.round() 方法。对于毫秒频率,请使用 freq 参数,其值设为 ‘ms’

首先,导入所需的库 −

import pandas as pd

创建一个 TimeDeltaIndex 对象。我们使用 'data' 参数设置类似 timedelta 的数据 −

tdIndex = pd.TimedeltaIndex(data =['10 day 5h 2 min 3us 10ns', '+22:39:19.999999',
'2 day 4h 03:08:02.000045', '+07:20:32.261811624'])

显示 TimedeltaIndex −

print("TimedeltaIndex...\n", tdIndex)

对 TimeDeltaIndex 日期使用毫秒频率的舍入操作。针对毫秒频率,我们使用了 'ms' −

print("\nPerforming round operation with milliseconds frequency...\n",
tdIndex.round(freq='ms'))

示例

以下是代码 −

import pandas as pd

# Create a TimeDeltaIndex object
# We have set the timedelta-like data using the 'data' parameter
tdIndex = pd.TimedeltaIndex(data =['10 day 5h 2 min 3us 10ns', '+22:39:19.999999',
'2 day 4h 03:08:02.000045', '+07:20:32.261811624'])

# display TimedeltaIndex
print("TimedeltaIndex...\n", tdIndex)

# Return a dataframe of the components of TimeDeltas
print("\nThe Dataframe of the components of TimeDeltas...\n", tdIndex.components)

# Round operation on TimeDeltaIndex date with milliseconds frequency
# For milliseconds frequency, we have used 'ms'
print("\nPerforming round operation with milliseconds frequency...\n",
tdIndex.round(freq='ms'))

输出

将生成以下代码 −

TimedeltaIndex...
TimedeltaIndex(['10 days 05:02:00.000003010', '0 days 22:39:19.999999',
'2 days 07:08:02.000045', '0 days 07:20:32.261811624'],
dtype='timedelta64[ns]', freq=None)

The Dataframe of the components of TimeDeltas...
   days hours minutes seconds milliseconds microseconds nanoseconds
0   10     5      2       0           0            3           10
1    0    22     39      19         999          999            0
2    2     7      8       2           0           45            0
3    0     7     20      32         261          811          624

Performing round operation with milliseconds frequency...
TimedeltaIndex([ '10 days 05:02:00', '0 days 22:39:20',
'2 days 07:08:02', '0 days 07:20:32.262000'],
dtype='timedelta64[ns]', freq=None)

更新日期: 2021 年 10 月 20 日

231 次浏览

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