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)
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