In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is
[(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as
arr['a'] and arr['b'].
Record arrays allow the fields to be accessed as members of the array, using
arr.a and arr.b.
numpy.recarray.var() function returns the variance of the array elements, along given axis.
numpy.recarray.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False)
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.
dtype : [data-type, optional] Type we desire while computing variance.
out : [ndarray, optional] A location into which the result is stored.
-> If provided, it must have a shape that the inputs broadcast to.
-> If not provided or None, a freshly-allocated array is returned.
ddof : [int, optional] Delta Degrees of Freedom”: the divisor used in the calculation is N – ddof, where N represents the number of elements. By default ddof is zero.
keepdims : [bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
Return : [ndarray] If out=None, returns a new array containing the variance; otherwise, a reference to the output array is returned.
Code #1 :
Input array : [[( 5., 2) ( 3., -4) ( 6., 9)] [( 9., 1) ( 5., 4) (-12., -7)]] Record array of float: [[ 5. 3. 6.] [ 9. 5. -12.]] Record array of int: [[ 2 -4 9] [ 1 4 -7]] Output array containing variance along axis 1: [ 1.55555556 82.88888889] Output array containing variance along axis 0: [ 4. 1. 81.] Output array containing variance along default axis : 46.22222222222222 Output array containing variance along axis 1: [28.22222222 21.55555556] Output array containing variance along axis 0: [ 0.25 16. 64. ] Output array containing variance along default axis : 27.138888888888882
- Python | numpy.cov() function
- Numpy MaskedArray.any() function | Python
- Numpy recarray.dot() function | Python
- Numpy size() function | Python
- Python | numpy.issubdtype() function
- Python | numpy.issubsctype() function
- Numpy recarray.all() function | Python
- Python | Numpy nanmedian() function
- Numpy recarray.mean() function | Python
- Numpy recarray.max() function | Python
- Numpy recarray.min() function | Python
- Numpy MaskedArray.all() function | Python
- Numpy MaskedArray.dot() function | Python
- Python | numpy.issctype() function
- Numpy recarray.any() function | Python
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.