Python Pandas - 对具有微秒频率的 TimeDeltaIndex 执行向下取整运算


要对具有微秒频率的 TimeDeltaIndex 执行向下取整运算,请使用 **TimeDeltaIndex.floor()** 方法。对于微秒频率,请使用值为 **‘us’** 的 **freq** 参数。

首先,导入所需的库:

import pandas as pd

创建一个 TimeDeltaIndex 对象。我们使用 'data' 参数设置了类似 timedelta 的数据:

tdIndex = pd.TimedeltaIndex(data =['5 day 8h 20min 35us 45ns', '+17:42:19.999999',
'7 day 3h 08:16:02.000055', '+22:35:25.999999'])

显示 TimedeltaIndex:

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

对 TimeDeltaIndex 日期进行具有微秒频率的向下取整运算。对于微秒频率,我们使用了 'us':

print("\nPerforming Floor operation with microseconds frequency...\n",
tdIndex.floor(freq='us'))

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 =['5 day 8h 20min 35us 45ns', '+17:42:19.999999',
'7 day 3h 08:16:02.000055', '+22:35:25.999999'])

# 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)

# Floor operation on TimeDeltaIndex date with microseconds frequency
# For microseconds frequency, we have used 'us'
print("\nPerforming Floor operation with microseconds frequency...\n",
tdIndex.floor(freq='us'))

输出

这将产生以下代码:

TimedeltaIndex...
TimedeltaIndex(['5 days 08:20:00.000035045', '0 days 17:42:19.999999',
'7 days 11:16:02.000055', '0 days 22:35:25.999999'],
dtype='timedelta64[ns]', freq=None)

The Dataframe of the components of TimeDeltas...
   days hours minutes seconds milliseconds microseconds nanoseconds
0    5     8      20      0           0            35         45
1    0    17      42     19         999           999          0
2    7    11      16      2           0            55          0
3    0    22      35     25         999           999          0

Performing Floor operation with microseconds frequency...
TimedeltaIndex(['5 days 08:20:00.000035', '0 days 17:42:19.999999',
'7 days 11:16:02.000055', '0 days 22:35:25.999999'],
dtype='timedelta64[ns]', freq=None)

更新于:2021年10月20日

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