Python | Pandas Series.rolling()

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.rolling() function is a very useful function. It Provides rolling window calculations over the underlying data in the given Series object.

Syntax: Series.rolling(window, min_periods=None, center=False, win_type=None, on=None, axis=0, closed=None) Parameter : window : Size of the moving window min_periods : Minimum number of observations in window required to have a value center : Set the labels at the center of the window. win_type : Provide a window type. on : str, optional axis : int or str, default 0 closed : Make the interval closed on the ‘right’, ‘left’, ‘both’ or ‘neither’ endpoints. Returns : a Window or Rolling sub-classed for the particular operation

Example #1: Use Series.rolling() function to find the rolling window sum of the underlying data for the given Series object. The size of the rolling window should be 2 and the weightage of each element should be same. Python3

# 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.rolling() function to find the sum of the underlying data having a window size of 2. Python3

# Find sum over a window size of 2
result = sr.rolling(2).sum()

# Print the returned Series object
print(result)

Output : As we can see in the output, the Series.rolling() function has successfully returned a series object having found the sum of the underlying data over a window size of 2. Notice the first value is a missing value as there was no element previous to it so the sum could not be performed.   Example #2: Use Series.rolling() function to find the rolling window sum of the underlying data for the given Series object. The size of the rolling window should be 2 and the rolling window type should be 'triang'. Python3

# 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.rolling() function to find the sum of the underlying data having a window size of 2. Python3

# Find sum over a window size of 2
# We have also provided the window type
result = sr.rolling(2, win_type ='triang').sum()

# Print the returned Series object
print(result)

Output : As we can see in the output, the Series.rolling() function has successfully returned a series object having found the sum of the underlying data over a window size of 2. Notice the first value is a missing value as there was no element previous to it so the sum could not be performed.