How to find median in python using numpy

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    numpy.median(arr, axis = None) : Compute the median of the given data (array elements) along the specified axis.

    How to calculate median?

    • Given data points.
    • Arrange them in ascending order
    • Median = middle term if total no. of terms are odd.
    • Median = Average of the terms in the middle (if total no. of terms are even)

    Parameters :
    arr : [array_like]input array.
    axis : [int or tuples of int]axis along which we want to calculate the median. Otherwise, it will consider arr to be flattened(works on all the axis). axis = 0 means along the column and axis = 1 means working 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 median.

    Results : Median of the array (a scalar value if axis is none) or array with median values along specified axis.

    Code #1:

    import numpy as np

    arr = [20, 2, 7, 1, 34]

    print("arr : ", arr) 

    print("median of arr : ", np.median(arr))

    Output :

    arr :  [20, 2, 7, 1, 34]
    median of arr :  7.0
    

     
    Code #2:

    import numpy as np

    arr = [[14, 17, 12, 33, 44],  

           [15, 6, 27, 8, 19], 

           [23, 2, 54, 1, 4, ]] 

    print("\nmedian of arr, axis = None : ", np.median(arr)) 

    print("\nmedian of arr, axis = 0 : ", np.median(arr, axis = 0)) 

    print("\nmedian of arr, axis = 1 : ", np.median(arr, axis = 1))

    out_arr = np.arange(3)

    print("\nout_arr : ", out_arr) 

    print("median of arr, axis = 1 : "

          np.median(arr, axis = 1, out = out_arr))

    Output :

    median of arr, axis = None :  15.0
    
    median of arr, axis = 0 :  [15.  6. 27.  8. 19.]
    
    median of arr, axis = 1 :  [17. 15.  4.]
    
    out_arr :  [0 1 2]
    median of arr, axis = 1 :  [17 15  4]
    

    numpy.median(a, axis=None, out=None, overwrite_input=False, keepdims=False)[source]#

    Compute the median along the specified axis.

    Returns the median of the array elements.

    Parametersaarray_like

    Input array or object that can be converted to an array.

    axis{int, sequence of int, None}, optional

    Axis or axes along which the medians are computed. The default is to compute the median along a flattened version of the array. A sequence of axes is supported since version 1.9.0.

    outndarray, optional

    Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type (of the output) will be cast if necessary.

    overwrite_inputbool, optional

    If True, then allow use of memory of input array a for calculations. The input array will be modified by the call to median. This will save memory when you do not need to preserve the contents of the input array. Treat the input as undefined, but it will probably be fully or partially sorted. Default is False. If overwrite_input is True and a is not already an ndarray, an error will be raised.

    keepdimsbool, 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 original arr.

    New in version 1.9.0.

    Returns medianndarray

    A new array holding the result. If the input contains integers or floats smaller than float64, then the output data-type is np.float64. Otherwise, the data-type of the output is the same as that of the input. If out is specified, that array is returned instead.

    Notes

    Given a vector V of length N, the median of V is the middle value of a sorted copy of V, V_sorted - i e., V_sorted[(N-1)/2], when N is odd, and the average of the two middle values of V_sorted when N is even.

    Examples

    >>> a = np.array([[10, 7, 4], [3, 2, 1]])
    >>> a
    array([[10,  7,  4],
           [ 3,  2,  1]])
    >>> np.median(a)
    3.5
    >>> np.median(a, axis=0)
    array([6.5, 4.5, 2.5])
    >>> np.median(a, axis=1)
    array([7.,  2.])
    >>> m = np.median(a, axis=0)
    >>> out = np.zeros_like(m)
    >>> np.median(a, axis=0, out=m)
    array([6.5,  4.5,  2.5])
    >>> m
    array([6.5,  4.5,  2.5])
    >>> b = a.copy()
    >>> np.median(b, axis=1, overwrite_input=True)
    array([7.,  2.])
    >>> assert not np.all(a==b)
    >>> b = a.copy()
    >>> np.median(b, axis=None, overwrite_input=True)
    3.5
    >>> assert not np.all(a==b)
    

    Does NumPy have a median function?

    The NumPy median function computes the median of the values in a NumPy array. Note that the NumPy median function will also operate on “array-like objects” like Python lists.

    How do you find the median in Python?

    median() method calculates the median (middle value) of the given data set. This method also sorts the data in ascending order before calculating the median. Tip: The mathematical formula for Median is: Median = {(n + 1) / 2}th value, where n is the number of values in a set of data.

    How do you find the mean in NumPy Python?

    mean() function is used to compute the arithmetic mean along the specified axis..
    import numpy as np..
    a = np. array([[1, 2], [3, 4]]).
    b=np. mean(a).
    x = np. array([[5, 6], [7, 34]]).
    y=np. mean(x).

    How do I calculate the median?

    The median is calculated by arranging the scores in numerical order, dividing the total number of scores by two, then rounding that number up if using an odd number of scores to get the position of the median or, if using an even number of scores, by averaging the number in that position and the next position.