Series.rolling()
functionThe pandas Series.rolling()
function offers a rolling windows function over data in the given Series.
Series.rolling(window, min_periods=None, center=False, win_type=None, axis=0, closed=None)
window
: It represents the size of the moving window.
min_periods
: It represents the minimum number of observations needed to have a value in the window. The default is None
.
center
: It sets the labels of the window. The default is False
. If False
, the window labels are set at the right edge of the window index. Otherwise, the window labels are set at the center of the window index.
win_type
: It indicates the window type.
axis
: It can be int
or string
. The default value is 0
. If 0
or index
, the operation is performed across the rows. If 1
or columns
, the operation is performed across the columns.
closed
: It is used to close the interval on the ‘right’, ‘left’, ‘both’ or ‘neither’ endpoints.
The following code will demonstrate how to use the Series.rolling()
function in pandas.
import pandas as pd # create Series my_series = pd.Series([17, 9, 28, 15, 23, 7, 14]) # using rolling() to compute sum() print(my_series.rolling(2).sum())
In the code above, we see the following:
Lines 1–2: We import the pandas
library.
Line 5: We create the series, my_series
.
Line 9: We calculate the sum of data in the series over a window size of 2 using the rolling()
function.
Note: A NaN was returned for the first element in the series since there is no element before it, making the
sum
operation impossible.
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