Numpy recarray.min() function | Python

Last Updated : 27 Sep, 2019
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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.min() function returns the minimum of record array or minimum along an axis.
Syntax : numpy.recarray.min(axis=None, out=None, keepdims=False) Parameters: axis : [None or int or tuple of ints, optional] Axis or axes along which to operate. By default, flattened input is used. 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. 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 or scalar] Minimum of record array. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension arr.ndim - 1.
Code #1 : Python3 
# Python program explaining
# numpy.recarray.min() method 

# importing numpy as geek
import numpy as geek

# creating input array with 2 different field 
in_arr = geek.array([[(5.0, 2), (3.0, 4), (6.0, 8)],
                     [(9.0, 1), (5.0, 4), (-12.0, 7)]],
                     dtype =[('a', float), ('b', int)])

print ("Input array : ", in_arr)

# convert it to a record array,
# using arr.view(np.recarray)
rec_arr = in_arr.view(geek.recarray)
print("Record array of float: ", rec_arr.a)
print("Record array of int: ", rec_arr.b)

# applying recarray.min methods
# to float record array along default axis 
# i, e along flattened array
out_arr1 = rec_arr.a.min()
# Minimum of the flattened array 
print("\nMin of float record array, axis = None : ", out_arr1) 


# applying recarray.min methods
# to float record array along axis 0
# i, e along vertical
out_arr2 = rec_arr.a.min(axis = 0)
# Minimum along 0 axis
print("\nMin of float record array, axis = 0 : ", out_arr2)


# applying recarray.min methods
# to float record array along axis 1
# i, e along horizontal
out_arr3 = rec_arr.a.min(axis = 1)
# Minimum along 0 axis
print("\nMin of float record array, axis = 1 : ", out_arr3)


# applying recarray.min methods
# to int record array along default axis 
# i, e along flattened array
out_arr4 = rec_arr.b.min()
# Minimum of the flattened array 
print("\nMin of int record array, axis = None : ", out_arr4) 


# applying recarray.min methods
# to int record array along axis 0
# i, e along vertical
out_arr5 = rec_arr.b.min(axis = 0)
# Minimum along 0 axis
print("\nMin of int record array, axis = 0 : ", out_arr5)


# applying recarray.min methods
# to int record array along axis 1
# i, e along horizontal
out_arr6 = rec_arr.b.min(axis = 1)
# Minimum along 0 axis
print("\nMin of int record array, axis = 1 : ", out_arr6)
Output: 
Input array :  [[(  5., 2) (  3., 4) (  6., 8)]
 [(  9., 1) (  5., 4) (-12., 7)]]
Record array of float:  [[  5.   3.   6.]
 [  9.   5. -12.]]
Record array of int:  [[2 4 8]
 [1 4 7]]

Min of float record array, axis = None :  -12.0

Min of float record array, axis = 0 :  [  5.   3. -12.]

Min of float record array, axis = 1 :  [  3. -12.]

Min of int record array, axis = None :  1

Min of int record array, axis = 0 :  [1 4 7]

Min of int record array, axis = 1 :  [2 1]

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