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numpy.nansum() in Python
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numpy.nanvar() in Python

Last Updated : 03 Dec, 2018
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numpy.nanvar(arr, axis = None) : Compute the variance of the given data (array elements) along the specified axis(if any), while ignoring NaN values. Example :
x = 1 1 1 1 1 Standard Deviation = 0 . Variance = 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.
Parameters : arr : [array_like] input array. axis : [int or tuples of int]axis along which we want to calculate the variance. Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0 means variance along the column and axis = 1 means variance 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 variance. Results : Variance of the array (a scalar value if axis is none) or array with variance values along specified axis; while ignoring NaN values.
Code #1: Python3 1== 
# Python Program illustrating  # numpy.nanvar() method  import numpy as np       # 1D array  arr = [20, 2, np.nan, 1, 34]   print("arr : ", arr)  print("\nnanvar of arr : ", np.nanvar(arr))   print("var of arr : ", np.var(arr))   print("\nnanvar of arr : ", np.nanvar(arr, dtype = np.float32))  print("var of arr : ", np.var(arr, dtype = np.float32))
Output : 
  arr :  [20, 2, nan, 1, 34]    nanvar of arr :  187.1875  var of arr :  nan    nanvar of arr :  187.1875  var of arr :  nan
  Code #2: Python3 1== 
# Python Program illustrating  # numpy.nanvar() method  import numpy as np        # 2D array  arr = [[2, 2, 2, 2, 2],      [15, 6, np.nan, 8, 2],      [23, 2, 54, 1, 2, ],      [np.nan, 44, 34, 7, 2]]        # nanvar of the flattened array  print("\nnanvar of arr, axis = None : ", np.nanvar(arr))   print("\nvar of arr, axis = None : ", np.var(arr))        # nanvar along the axis = 0  print("\nnanvar of arr, axis = 0 : \n", np.nanvar(arr, axis = 0))   print("\nvar of arr, axis = 0 : ", np.var(arr, axis = 0))   # nanvar along the axis = 1  print("\nnanvar of arr, axis = 1 : ", np.nanvar(arr, axis = 1))
Output : 
  nanvar of arr, axis = None :  249.88888888888889    var of arr, axis = None :  nan    nanvar of arr, axis = 0 :    [ 74.88888889 312.75       458.66666667   9.25         0.        ]    var of arr, axis = 0 :  [   nan 312.75    nan   9.25   0.  ]    nanvar of arr, axis = 1 :  [  0.      22.1875 421.84   313.1875]

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numpy.nansum() in Python
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mohit gupta_omg :)
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Article Tags :
  • Python
  • Python-numpy
  • Python numpy-Statistics Functions
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