Python是进行数据分析的一种出色语言，主要是因为以数据为中心的python软件包具有奇妙的生态系统。 Pandas是其中的一种，使导入和分析数据更加容易。

Pandas dataframe.shift()函数根据需要的周期数移动索引，并带有可选的时间频率。该函数采用称为周期的标量参数，该参数表示要在所需轴上进行的平移次数。处理时间序列数据时，此功能非常有用。

用法：DataFrame.shift(periods=1, freq=None, axis=0)

参数:

periods: Number of periods to move, can be positive or negative

freq: DateOffset, timedelta, or time rule string, optional Increment to use from the tseries module or time rule (e.g. ‘EOM’). See Notes

axis: {0 or ‘index’, 1 or ‘columns’}

返回：shifted：DataFrame

范例1：采用shift()在时间序列数据中将索引轴移动2个周期的功能

# importing pandas as pd

import pandas as pd

# Creating row index values for our data frame

# We have taken time frequency to be of 12 hours interval

# We are generating five index value using "period = 5" parameter

ind = pd.date_range('01 / 01 / 2000', periods = 5, freq ='12H')

# Creating a dataframe with 4 columns

# using "ind" as the index for our dataframe

df = pd.DataFrame({"A":[1, 2, 3, 4, 5],

"B":[10, 20, 30, 40, 50],

"C":[11, 22, 33, 44, 55],

"D":[12, 24, 51, 36, 2]},

index = ind)

# Print the dataframe

df

让我们使用dataframe.shift()使索引轴向正方向移动2个周期的功能

# shift index axis by two periods in positive direction

# axis = 0 is set by default

df.shift(2, axis = 0)

让索引轴在负方向上移动一段时间

# shift index axis by two periods in negative direction

# axis = 0 is set by default

df.shift(-2, axis = 0)

输出：

范例2：采用shift()用于在时间序列数据中将列轴移动2个周期

# importing pandas as pd

import pandas as pd

# Creating row index values for our data frame

# We have taken time frequency to be of 12 hours interval

# We are generating five index value using "period = 5" parameter

ind = pd.date_range('01 / 01 / 2000', periods = 5, freq ='12H')

# Creating a dataframe with 4 columns

# using "ind" as the index for our dataframe

df = pd.DataFrame({"A":[1, 2, 3, 4, 5],

"B":[10, 20, 30, 40, 50],

"C":[11, 22, 33, 44, 55],

"D":[12, 24, 51, 36, 2]},

index = ind)

# Print the dataframe

df

让我们使用dataframe.shift()沿正方向将列轴移动2个周期的功能

# shift column axis by two periods in positive direction

df.shift(2, axis = 1)

让列轴在负方向上移动一段时间

# shift column axis by two periods in negative direction

df.shift(-2, axis = 0)

输出：