Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas dataframe.shift()
function Shift index by desired number of periods with an optional time freq. This function takes a scalar parameter called period, which represents the number of shifts to be made over the desired axis. This function is very helpful when dealing with time-series data.
Syntax:DataFrame.shift(periods=1, freq=None, axis=0)
Parameters :
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’}Return : shifted : DataFrame
Example #1: Use shift()
function to shift the index axis by 2 periods in a time-series data
# 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 |
Lets use the dataframe.shift()
function to shift the index axis by 2 periods in positive direction
# shift index axis by two periods in positive direction # axis = 0 is set by default df.shift( 2 , axis = 0 ) |
Lets shift the index axis in negative direction by some periods
# shift index axis by two periods in negative direction # axis = 0 is set by default df.shift( - 2 , axis = 0 ) |
Output :
Example #2: Use shift()
function to shift the column axis by 2 periods in a time-series data
# 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 |
Lets use the dataframe.shift()
function to shift the column axis by 2 periods in positive direction
# shift column axis by two periods in positive direction df.shift( 2 , axis = 1 ) |
Lets shift the column axis in negative direction by some periods
# shift column axis by two periods in negative direction df.shift( - 2 , axis = 0 ) |
Output :
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