def make_future_dataframe(self, periods, freq=’D’, include_history=True):
“””Simulate the trend using the extrapolated generative model.
Parameters
pd.Dataframe that extends forward from the end of self.history for the
requested number of periods.
“””
make_future_dataframe()参数说明：
- periods: 向前预测步数
- freq: 预测单位小时为’H’，天为’D’，月为’M’
- include_history: 是否包含历史数据的预测
=====================================================================
make_future_dataframe（）准备预测的数据框架，该函数的定义如下：
periods:指定要预测的时长，要根据freq这个参数去设置。假如freq=’D’，那么粒度为天，periods则指定要预测未来多少天的数据。如果freq=’H’,则periods指定要预测未来多少小时的数据（当然，要在框架支持粒度为小时的前提下才能运用）。
include_history：是否包含历史数据，保持默认就好。
=========================================================================
若有以下时间序列，如何在每月月末显示该月数据的均值？
>>>  import pandas as pd
>>>  import numpy as np
>>> ts  = pd.Series(np.random.randint( 0 , 10 , 10 ))
>>> ts.index  = pd.date_range(start = '2020-1-15' ,periods = 10 ,freq = '10D' )
>>> ts
2020 - 01 - 15 7
2020 - 01 - 25 1
2020 - 02 - 04 8
2020 - 02 - 14 7
2020 - 02 - 24 1
2020 - 03 - 05 3
2020 - 03 - 15 6
2020 - 03 - 25 8
2020 - 04 - 04 6
2020 - 04 - 14 1
Freq:  10D , dtype: int32
====================================================================
pd.date_range(start=’2022-08-14 08:01:00′, periods=24,freq=’5T’)
DatetimeIndex([‘2022-08-14 08:01:00’, ‘2022-08-14 08:06:00’,
‘2022-08-14 08:11:00’, ‘2022-08-14 08:16:00’,
‘2022-08-14 08:21:00’, ‘2022-08-14 08:26:00’,
‘2022-08-14 08:31:00’, ‘2022-08-14 08:36:00’,
‘2022-08-14 08:41:00’, ‘2022-08-14 08:46:00’,
‘2022-08-14 08:51:00’, ‘2022-08-14 08:56:00’,
‘2022-08-14 09:01:00’, ‘2022-08-14 09:06:00’,
‘2022-08-14 09:11:00’, ‘2022-08-14 09:16:00’,
‘2022-08-14 09:21:00’, ‘2022-08-14 09:26:00’,
‘2022-08-14 09:31:00’, ‘2022-08-14 09:36:00’,
‘2022-08-14 09:41:00’, ‘2022-08-14 09:46:00’,
‘2022-08-14 09:51:00’, ‘2022-08-14 09:56:00′],
dtype=’datetime64[ns]’, freq=’5T’)Original: https://blog.csdn.net/lizz2276/article/details/126331642
Author: lizz2276
Title: prophet make_future_dataframe()参数说明
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