Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.
Pandas DataFrame.tshift() function is used toShift the time index, using the index’s frequency if available in the given dataframe.
Syntax: DataFrame.tshift(periods=1, freq=None, axis=0)
Parameter :
periods : Number of periods to move, can be positive or negative
freq : Increment to use from the tseries module or time rule (e.g. ‘EOM’)
axis : Corresponds to the axis that contains the IndexReturns : shifted : NDFrame
Example #1: Use DataFrame.tshift() function to shift the Datetime based Index of the given dataframe by 5 hours.
# importing pandas as pd import pandas as pd # Creating the DataFrame df = pd.DataFrame({'Weight':[45, 88, 56, 15, 71], 'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age':[14, 25, 55, 8, 21]}) # Create the index index_ = pd.date_range('2010-10-09 08:45', periods = 5, freq ='H') # Set the index df.index = index_ # Print the DataFrame print(df) |
Output :
Now we will use DataFrame.tshift() function to shift the Datetime based Index of the given dataframe by 5 hours. We will pass ‘5H’ as the freq value to the function.
# Shift by 5 hours result = df.tshift(freq = '5H') # Print the result print(result) |
Output :
As we can see in the output, the DataFrame.tshift() function has successfully shifted the Datetime based index of the given dataframe by the specified frequency.
Example #2 : Use DataFrame.tshift() function to shift the Datetime based Index of the given dataframe by -30 periods.
# importing pandas as pd import pandas as pd # Creating the DataFrame df = pd.DataFrame({'Weight':[45, 88, 56, 15, 71], 'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age':[14, 25, 55, 8, 21]}) # Create the index index_ = pd.date_range('2010-10-09 08:45', periods = 5, freq ='H') # Set the index df.index = index_ # Print the DataFrame print(df) |
Output :
Now we will use DataFrame.tshift() function to shift the Datetime based Index of the given dataframe by -30 periods. This will shift the index on the same frequency by 30 periods in the past.
# Shift by -30 periods result = df.tshift(periods = -30) # Print the result print(result) |
Output :
As we can see in the output, the DataFrame.tshift() function has successfully shifted the Datetime based index of the given dataframe by the specified periods.
