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法律研究Python Pandas - 從 TimeDeltaIndex 建立一個序列
使用 to_series() 方法從 Pandas 中的 TimeDeltaIndex 建立一個系列。
首先，匯入需要的庫 −
import pandas as pd
建立一個 TimeDeltaIndex 物件。我們使用 'data' 引數設定類 timedelta 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', '+21:15:45.999999'])
將 TimeDeltaIndex 轉換為 Series −
print("\nTimeDeltaIndex to series...\n", tdIndex.to_series())
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', '+21:15:45.999999'])
# 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)
# Return TimeDeltaIndex as object ndarray
print("\nReturn TimeDeltaIndex as object ndarray of datetime.datetime objects...\n",
tdIndex.to_pytimedelta())
# Convert TimeDeltaIndex to Series
print("\nTimeDeltaIndex to series...\n", tdIndex.to_series())輸出
這會產生以下程式碼 −
TimedeltaIndex... TimedeltaIndex(['10 days 05:02:00.000003010', '0 days 22:39:19.999999', '2 days 07:08:02.000045', '0 days 21:15:45.999999'], 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 21 15 45 999 999 0 Return TimeDeltaIndex as object ndarray of datetime.datetime objects... [datetime.timedelta(days=10, seconds=18120, microseconds=3) datetime.timedelta(seconds=81559, microseconds=999999) datetime.timedelta(days=2, seconds=25682, microseconds=45) datetime.timedelta(seconds=76545, microseconds=999999)] TimeDeltaIndex to series... 10 days 05:02:00.000003010 10 days 05:02:00.000003010 0 days 22:39:19.999999 0 days 22:39:19.999999 2 days 07:08:02.000045 2 days 07:08:02.000045 0 days 21:15:45.999999 0 days 21:15:45.999999 dtype: timedelta64[ns]
更新於：19-10-2021
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