Python Pandas - 對秒頻 TimeDeltaIndex 物件執行向上取整運算


要對秒頻 TimeDeltaIndex 執行向上取整運算,請使用 **TimeDeltaIndex.ceil()** 方法。對於秒頻,請使用值為 **‘S’** 的 **freq** 引數。

首先,匯入所需的庫:

import pandas as pd

建立一個 TimeDeltaIndex 物件。我們使用 'data' 引數設定了類似時間增量的資料:

tdIndex = pd.TimedeltaIndex(data =['4 day 8h 20min 35us 45ns', '+17:42:19.999999',
'9 day 3h 08:16:02.000055', '+22:35:25.000075'])

顯示 TimedeltaIndex:

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

對 TimeDeltaIndex 日期執行秒頻的向上取整運算。對於秒頻,我們使用了 'S':

print("\nPerforming Ceil operation with seconds frequency...\n",
tdIndex.ceil(freq='S'))

示例

以下是程式碼:

import pandas as pd

# Create a TimeDeltaIndex object
# We have set the timedelta-like data using the 'data' parameter
tdIndex = pd.TimedeltaIndex(data =['4 day 8h 20min 35us 45ns', '+17:42:19.999999',
'9 day 3h 08:16:02.000055', '+22:35:25.000075'])

# 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)

# Ceil operation on TimeDeltaIndex date with seconds frequency
# For seconds frequency, we have used 'S'
print("\nPerforming Ceil operation with seconds frequency...\n",
tdIndex.ceil(freq='S'))

輸出

這將產生以下程式碼:

TimedeltaIndex...
TimedeltaIndex(['4 days 08:20:00.000035045', '0 days 17:42:19.999999',
'9 days 11:16:02.000055', '0 days 22:35:25.000075'],
dtype='timedelta64[ns]', freq=None)

The Dataframe of the components of TimeDeltas...
   days hours minutes seconds milliseconds microseconds nanoseconds
0    4     8      20       0           0           35          45
1    0    17      42      19         999          999           0
2    9    11      16       2           0           55           0
3    0    22      35      25           0           75           0

Performing Ceil operation with seconds frequency...
TimedeltaIndex(['4 days 08:20:01', '0 days 17:42:20', '9 days 11:16:03',
'0 days 22:35:26'],
dtype='timedelta64[ns]', freq=None)

更新於:2021年10月20日

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