## How do I find the Index of the smallest number in an array in python if I have multiple smallest numbers and want both indexes?

numpy argsort

get index of max value in numpy array python

numpy argpartition

numpy partition

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I have an array in which I want to find the index of the smallest elements. I have tried the following method:

distance = [2,3,2,5,4,7,6] a = distance.index(min(distance))

This returns 0, which is the index of the first smallest distance. However, I want to find all such instances, 0 and 2. How can I do this in Python?

You may enumerate array elements and extract their indexes if the condition holds:

min_value = min(distance) [i for i,n in enumerate(distance) if n==min_value] #[0,2]

**Find K smallest and largest values and its indices in a numpy array ,** To find the maximum and minimum value in an array you can use numpy argmax and argmin function. These two functions( argmax and argmin )� Python Program to find the Smallest Number in a List Example 2. This python program is the same as above. But this time, we are allowing the user to enter the length of a List.

Use np.where to get all the indexes that match a given value:

import numpy as np distance = np.array([2,3,2,5,4,7,6]) np.where(distance == np.min(distance))[0] Out[1]: array([0, 2])

Numpy outperforms other methods as the size of the array grows:

##### Results of TimeIt comparison test, adapted from Yannic Hamann's code below

Length of Array x 7 Method 1 10 20 50 100 1000 Sorted Enumerate 2.47 16.291 33.643 List Comprehension 1.058 4.745 8.843 24.792 Numpy 5.212 5.562 5.931 6.22 6.441 6.055 Defaultdict 2.376 9.061 16.116 39.299

**Python - Find the indices for k Smallest elements,** Sometimes, while working with Python lists, we can have a problem in which we This task can occur in many domains such as web development and while Let's discuss a certain way to find indices of K smallest elements in list. If you like GeeksforGeeks and would like to contribute, you can also write� To find largest and smallest number in a list. Approach : Read input number asking for length of the list using input() or raw_input(). Initialise an empty list lst = []. Read each number using a

Surprisingly the `numpy`

answer seems to be the slowest.

Update: Depends on the size of the input list.

import numpy as np import timeit from collections import defaultdict def weird_function_so_bad_to_read(distance): se = sorted(enumerate(distance), key=lambda x: x[1]) smallest_numb = se[0][1] # careful exceptions when list is empty return [x for x in se if smallest_numb == x[1]] # t1 = 1.8322973089525476 def pythonic_way(distance): min_value = min(distance) return [i for i, n in enumerate(distance) if n == min_value] # t2 = 0.8458914929069579 def fastest_dont_even_have_to_measure(np_distance): # np_distance = np.array([2, 3, 2, 5, 4, 7, 6]) min_v = np.min(np_distance) return np.where(np_distance == min_v)[0] # t3 = 4.247801031917334 def dd_answer_was_my_first_guess_too(distance): d = defaultdict(list) # a dictionary where every value is a list by default for idx, num in enumerate(distance): d[num].append(idx) # for each number append the value of the index return d.get(min(distance)) # t4 = 1.8876687170704827 def wrapper(func, *args, **kwargs): def wrapped(): return func(*args, **kwargs) return wrapped distance = [2, 3, 2, 5, 4, 7, 6] t1 = wrapper(weird_function_so_bad_to_read, distance) t2 = wrapper(pythonic_way, distance) t3 = wrapper(fastest_dont_even_have_to_measure, np.array(distance)) t4 = wrapper(dd_answer_was_my_first_guess_too, distance) print(timeit.timeit(t1)) print(timeit.timeit(t2)) print(timeit.timeit(t3)) print(timeit.timeit(t4))

**numpy.amin(),** Python's numpy module provides a function to get the minimum If it's provided then it will return for array of min values along the axis i.e. Get the array of indices of minimum value in numpy array using numpy.where() i.e. Tuple of arrays returned : (array([0, 2], dtype=int32), array([0, 2], dtype=int32)). C Program to Find Smallest Number in an Array. In this C Program to find the smallest number in an array, we declared 1 One Dimensional Arrays a[] of size 10.We also declared i to iterate the Array elements, the Smallest variable to hold the smallest element in an Array.

We can use an interim dict to store indices of the list and then just fetch the minimum value of distance from it. We will also use a simple for-loop here so that you can understand what is happening step by step.

from collections import defaultdict d = defaultdict(list) # a dictionary where every value is a list by default for idx, num in enumerate(distance): d[num].append(idx) # for each number append the value of the index d.get(min(distance)) # fetch the indices of the min number from our dict [0, 2]

**How do I find the indices of the maximum (or minimum) value of my ,** Learn more about maximum, minimum, max, min, index, array, matrix, find, I would like to know how to find the indices of just the maximum (or minimum) value. The "min" and "max" functions in MATLAB return the index of the minimum and maximum values, respectively, I got two indices, both have the same value. Given a list of numbers, the task is to write a Python program to find the smallest number in given list. Examples: Input : list1 = [10, 20, 4] Output : 4 Input : list2 = [20, 10, 20, 1, 100] Output : 1

You can also do the following `list comprehension`

distance = [2,3,2,5,4,7,6] min_distance = min(distance) [index for index, val in enumerate(distance) if val == min_distance] >>> [0, 2]

**Chapter 7: Arrays,** We need a way to declare many variables in one step and then be able to store and access Like Strings, arrays use zero-based indexing, that is, array indexes start with 0. If we changed the numbers array to have a different number of elements, this code sort(array), rearranges the values to go from smallest to largest. Java program to find largest and second largest in an array: Find the index of the largest number in an array: find largest and smallest number in an array in java: find the second smallest number in an array in java: Find the index of the smallest number in an array: Spring mvc hello world example for beginners: Spring MVC tutorial with examples

**8.6. array — Efficient arrays of numeric values — Python 2.7.18 ,** On narrow Unicode builds this is 2-bytes, on wide builds this is 4-bytes. Array objects support the ordinary sequence operations of indexing, slicing, When using slice assignment, the assigned value must be an array object with the Return the smallest i such that i is the index of the first occurrence of x in the array . Python | Largest, Smallest, Second Largest, Second Smallest in a List 29-11-2017 Since, unlike other programming languages, Python does not have arrays, instead, it has list.

**Sorting Arrays,** This section covers algorithms related to sorting values in NumPy arrays. science courses: if you've ever taken one, you probably have had dreams (or, For example, a simple selection sort repeatedly finds the minimum value from a list, [1 2 3 4 5]. A related function is argsort , which instead returns the indices of the� As our array arr is a flat 1D array, so returned tuple will contain only one array of indices and contents of the returned array result[0] are, [ 4 7 11] Get the first index of element with value 15,

**9. Lists — How to Think Like a Computer Scientist: Learning with ,** A list is an ordered set of values, where each value is identified by an index. With all these ways to create lists, it would be disappointing if we couldn't assign list Since strings are immutable, Python optimizes resources by making two names Since variables refer to objects, if we assign one variable to another, both� In this article we will discuss how to find the minimum or smallest value in a Numpy array and it’s indices using numpy.amin(). numpy.amin() Python’s numpy module provides a function to get the minimum value from a Numpy array i.e.

##### Comments

- get the smallest number, and then linearly iterate, get all the indexes for that number.
- Why would you calculate the minimum for every iteration?
- @YannicHamann Nothing surprising at all. I ran these tests before posting my answer. NumPy is not a silver bullet.
- Interesting. I would not have expected that. I wonder why that is the case?
- when you compare distance of the type
`numpy.ndarray`

with an integer it always evaluates the FULL array. - I think this brings up an important point: numpy shines in efficient computation with very large arrays. For small arrays, numpy may not be the most efficient, as you have clearly pointed out. But numpy is much more scalable than most other methods. This discussion contains some relevant explanation.
- No problem. I made the plot above in Excel, because it was quick.
- I re-made the plot using Matplotlib.
- I ran some additional tests using your code which show how numpy performs well even as the array size increases dramatically.
- How is this different from my previously posted answer?
- @DYZ I think we both posted the answer at the same time. Or do you have any reason to suggest that my answer came from your? What if I turned around and asked you the same question?
- Calculating the minimum for every iteration seems wasteful in both of your answers.