  # numpy.std () in Python

Standard deviation (SD) is measured as the spread of the distribution of the data in a given dataset.

For example:

` x = 1 1 1 1 1 Standard Deviation = 0. y = 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4  Step 1:  Mean of distribution 4 = 7  Step 2:  Summation of (x - x.mean ()) ** 2 = 178  Step 3:  Finding Mean = 178/20 = 8.9 This Result is  Variance.   Step 4:  Standard Deviation = sqrt (Variance) = sqrt (8.9) = 2.983 .. `

Parameters:
arr: [array_like] input array.
axis: [int or tuples of int] axis along which we want to calculate the standard deviation. Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0 means SD along the column and axis = 1 means SD along the row.
out: [ndarray, optional] Different array in which we want to place the result. The array must have the same dimensions as expected output.
dtype: [data-type, optional] Type we desire while computing SD.

Results: Standard Deviation of the array (a scalar value if axis is none) or array with standard deviation values ​​along specified axis.

Code # 1:

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` # Python program illustrating # numpy.std () method import numpy as np    # 1D array arr = [ 20 , 2 , 7 , 1 , 34 ]   print ( "arr:" , arr)  print ( "std of arr:" , np.std (arr))   print ( "More precision with float32" ) print ( "std of arr:" , np.std (arr, dtype = np.float32))   pr int ( "More accuracy with float64" ) print ( "std of arr:" , np.std (arr, dtype = np.float64)) `

Output:

` arr: [20, 2, 7, 1, 34] std of arr: 12.576167937809991 More precision with float32 std of arr: 12.576168 More accuracy with float64 std of arr: 12.576167937809991 `

Code # 2:

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` # Python program illustrating # numpy.std () method import numpy as np  < / p>   # 2D array arr = [[[ 2 , 2 , 2 , 2 , 2 ],  [ 15 , 6 , 27 , 8 , 2 ],  [ 23 , 2  , 54 , 1 , 2 ,],  [ 11 , 44 , 34 , 7 , 2 ]]      # std flattened array print ( "std of arr, axis = None:" , np.std (arr))    # std along axis = 0 print ( "std of arr, axis = 0:" , np.std (arr, axis = 0 ))     # std along axis = 1 print ( "std of arr, axis = 1 : " , np.std (arr, axis = 1 )) `

Output:

` std of arr, axis = None: 15.3668474320532 std of arr, axis = 0: [7.56224173 17.68473918 18.59267329 3.04138127 0.] std of arr, axis = 1: [ 0.8.7772433 20.53874388 16.40243884] `