Python Pandas - 如何用微秒頻率舍入 TimeDeltaIndex


如需使用微秒頻率舍入 TimeDeltaIndex,請使用 TimeDeltaIndex.round() 方法。對於微秒頻率,將 freq 引數的值設為 ‘us’

首先,匯入所需的庫 −

import pandas as pd

建立一個 TimeDeltaIndex 物件。我們已使用 'data' 引數設定 timedelta 型別的資料 −

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'])

顯示 TimeDeltaIndex −

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

對帶微秒頻率的時間的 TimeDeltaIndex 日期進行舍入運算。對於微秒頻率,我們使用了 'us' −

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

示例

程式碼如下 −

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 microseconds frequency
# For microseconds frequency, we have used 'us'
print("\nPerforming round operation with microseconds frequency...\n",
tdIndex.round(freq='us'))

結果

將生成以下程式碼 −

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 microseconds frequency...
TimedeltaIndex(['10 days 05:02:00.000003', '0 days 22:39:19.999999',
'2 days 07:08:02.000045', '0 days 07:20:32.261812'],
dtype='timedelta64[ns]', freq=None)

更新於: 2021 年 10 月 20 日

334 次瀏覽

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