Python Pandas – 将 PeriodIndex 对象转换为 Timestamp 并设置频率
在本文中,我们将讨论如何将周期索引对象转换为时间戳并在Python编程语言中设置频率。
pandas PeriodIndex.to_timestamp() 方法用于将 PeriodIndex 对象转换为 Timestamp 并设置频率。频率可以使用方法的'freq'参数设置。
示例 1:
熊猫包已导入。使用 pd.PeriodIndex()函数创建一个周期索引对象,其中我们传入一个 DateTime 值数组,频率指定为“年”。周期索引对象将具有 YearEnd 类型的频率。 PeriodIndex 对象通过使用 pd.to_timestamp() 方法转换为时间戳对象。
Python3
# import packages
import pandas as pd
# Create a PeriodIndex object
# freq ='Y' represents year.
periodIndex = pd.PeriodIndex(['2022-12-21 09:30:20', '2021-11-20 06:45:40',
'2020-10-19 03:38:15', '2019-09-18 01:30:30'],
freq="Y")
print('period index object : ' + str(periodIndex))
print("frequency of the periodIndex object : ", periodIndex.freq)
# Display PeriodIndex frequency as string
print("frequency object as a string : ", periodIndex.freqstr)
# Converting PeriodIndex object to timestamp
print("Timestamp object : ", periodIndex.to_timestamp())
Python3
#import packages
import pandas as pd
# Create a PeriodIndex object
# freq ='Y' represents month.
periodIndex = pd.PeriodIndex(['2022-12-21 09:30:20', '2021-11-20 06:45:40',
'2020-10-19 03:38:15', '2019-09-18 01:30:30'],
freq="M")
print('period index object : ' + str(periodIndex))
print("frequency of the periodIndex object : ", periodIndex.freq)
# Display PeriodIndex frequency as string
print("frequency object as a string : ", periodIndex.freqstr)
# Converting PeriodIndex object to timestamp
print("Timestamp object : ", periodIndex.to_timestamp(freq='M'))
Python3
# import packages
import pandas as pd
# Create a PeriodIndex object
# freq ='Y' represents Day.
periodIndex = pd.PeriodIndex(['2022-12-21 09:30:20', '2021-11-20 06:45:40',
'2020-10-19 03:38:15', '2019-09-18 01:30:30'],
freq="D")
print('period index object : ' + str(periodIndex))
print("frequency of the periodIndex object : ", periodIndex.freq)
# Display PeriodIndex frequency as string
print("frequency object as a string : ", periodIndex.freqstr)
# Converting PeriodIndex object to timestamp
print("Timestamp object : ", periodIndex.to_timestamp(freq='D'))
输出:
示例 2:
在此示例中,我们将字符串“M”作为频率,这为我们提供了“MonthEnd”类型的周期索引对象。我们还指定时间戳对象的频率为“M”。
Python3
#import packages
import pandas as pd
# Create a PeriodIndex object
# freq ='Y' represents month.
periodIndex = pd.PeriodIndex(['2022-12-21 09:30:20', '2021-11-20 06:45:40',
'2020-10-19 03:38:15', '2019-09-18 01:30:30'],
freq="M")
print('period index object : ' + str(periodIndex))
print("frequency of the periodIndex object : ", periodIndex.freq)
# Display PeriodIndex frequency as string
print("frequency object as a string : ", periodIndex.freqstr)
# Converting PeriodIndex object to timestamp
print("Timestamp object : ", periodIndex.to_timestamp(freq='M'))
输出:
示例 3:
在此示例中,我们将字符串“D”作为频率,这为我们提供了“Day”类型的周期索引对象。我们还指定时间戳对象的频率为“D”。周期索引对象值与时间戳对象中的值完全匹配,因为我们将频率指定为“日”。
Python3
# import packages
import pandas as pd
# Create a PeriodIndex object
# freq ='Y' represents Day.
periodIndex = pd.PeriodIndex(['2022-12-21 09:30:20', '2021-11-20 06:45:40',
'2020-10-19 03:38:15', '2019-09-18 01:30:30'],
freq="D")
print('period index object : ' + str(periodIndex))
print("frequency of the periodIndex object : ", periodIndex.freq)
# Display PeriodIndex frequency as string
print("frequency object as a string : ", periodIndex.freqstr)
# Converting PeriodIndex object to timestamp
print("Timestamp object : ", periodIndex.to_timestamp(freq='D'))
输出: