Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.repeat() function repeat elements of a Series. It returns a new Series where each element of the current Series is repeated consecutively a given number of times.
Syntax: Series.repeat(repeats, axis=None)
Parameter :
repeats : The number of repetitions for each element.
axis : NoneReturns : repeated_series
Example #1: Use Series.repeat() function to repeat each value in the given Series object 2 times.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([10, 25, 3, 11, 24, 6]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.repeat() function to repeat each value of the given series object 2 times.
# repeat twice result = sr.repeat(repeats = 2) # Print the result print(result) |
Output :
As we can see in the output, the Series.repeat() function has returned a new series object where each values are repeated the specified number of times.
Example #2 : Use Series.repeat() function to repeat each value in the given Series object 3 times.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio']) # Create the Index index_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.repeat() function to repeat each value of the given series object 3 times.
# repeat twice result = sr.repeat(repeats = 3) # Print the result print(result) |
Output :
As we can see in the output, the Series.repeat() function has returned a new series object where each values are repeated the specified number of times.
