Python | Pandas Series.kurt()
Last Updated :
12 Feb, 2019
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.kurt()
function return unbiased kurtosis over requested axis using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). The result is normalized by N-1.
Syntax: Series.kurt(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)
Parameter :
axis : Axis for the function to be applied on.
skipna : Exclude NA/null values when computing the result.
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.
numeric_only : Include only float, int, boolean columns.
**kwargs : Additional keyword arguments to be passed to the function.
Returns : kurt : scalar or Series (if level specified)
Example #1: Use Series.kurt()
function to find the kurtosis of the underlying data of the given series object.
import pandas as pd
sr = pd.Series([ 10 , 25 , 3 , 25 , 24 , 6 ])
index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ]
sr.index = index_
print (sr)
|
Output :
Now we will use Series.kurt()
function to find the kurtosis of the underlying data of the given series object.
result = sr.kurt()
print (result)
|
Output :
As we can see in the output, the Series.kurt()
function has returned the kurtosis of the given series object.
Example #2 : Use Series.kurt()
function to find the kurtosis of the underlying data of the given series object.
import pandas as pd
sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , 84 , 32 , 10 , 5 , 24 , 32 ])
index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' )
sr.index = index_
print (sr)
|
Output :
Now we will use Series.kurt()
function to find the kurtosis of the underlying data of the given series object.
result = sr.kurt()
print (result)
|
Output :
As we can see in the output, the Series.kurt()
function has returned the kurtosis of the given series object.
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