scipy stats.mode() function | Python
scipy.stats.mode(array, axis=0)
function calculates the mode of the array elements along the specified axis of the array (list in python).
Its formula –
where,
l : Lower Boundary of modal class
h : Size of modal class
fm : Frequency corresponding to modal class
f1 : Frequency preceding to modal class
f2 : Frequency proceeding to modal class
Parameters :
array : Input array or object having the elements to calculate the mode.
axis : Axis along which the mode is to be computed. By default axis = 0
Returns : Modal values of the array elements based on the set parameters.
Code #1:
from scipy import stats
import numpy as np
arr1 = np.array([[ 1 , 3 , 27 , 13 , 21 , 9 ],
[ 8 , 12 , 8 , 4 , 7 , 10 ]])
print ( "Arithmetic mode is : \n" , stats.mode(arr1))
|
Output :
Arithmetic mode is :
ModeResult(mode=array([[1, 3, 8, 4, 7, 9]]), count=array([[1, 1, 1, 1, 1, 1]]))
Code #2: With multi-dimensional data
from scipy import stats
import numpy as np
arr1 = [[ 1 , 3 , 27 ],
[ 3 , 4 , 6 ],
[ 7 , 6 , 3 ],
[ 3 , 6 , 8 ]]
print ( "Arithmetic mode is : \n" , stats.mode(arr1))
print ( "\nArithmetic mode is : \n" , stats.mode(arr1, axis = None ))
print ( "\nArithmetic mode is : \n" , stats.mode(arr1, axis = 0 ))
print ( "\nArithmetic mode is : \n" , stats.mode(arr1, axis = 1 ))
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Output :
Arithmetic mode is :
ModeResult(mode=array([[3, 6, 3]]), count=array([[2, 2, 1]]))
Arithmetic mode is :
ModeResult(mode=array([3]), count=array([4]))
Arithmetic mode is :
ModeResult(mode=array([[3, 6, 3]]), count=array([[2, 2, 1]]))
Arithmetic mode is :
ModeResult(mode=array([[1],
[3],
[3],
[3]]), count=array([[1],
[1],
[1],
[1]]))
Last Updated :
11 Feb, 2019
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