Pythonic Way to Find Maximum Value and Its Index in a List

Pythonic way to find maximum value and its index in a list?

There are many options, for example:

import operator
index, value = max(enumerate(my_list), key=operator.itemgetter(1))

How to find the index of the max value in a list for Python?

• You are trying to find the index of i. It should be list_c[i].

Easy way/Better way is: idx_max = i. (Based on @Matthias comment above.)

• Use print to print the results and not return. You use return inside functions.
• Also your code doesn't work if list_c has all negative values because you are setting max_val to 0. You get a 0 always.

list_c = [-14, 7, -9, 2]

max_val = 0
idx_max = 0

for i in range(len(list_c)):
    if list_c[i] > max_val:
        max_val = list_c[i]
        idx_max = i

print(list_c, max_val, idx_max)

[-14, 7, -9, 2] 7 1

How to find all positions of the maximum value in a list?

>>> m = max(a)
>>> [i for i, j in enumerate(a) if j == m]
[9, 12]

How can I get the index of max values in list and then print the values from another list with max's index?

events = [1, 2, 3, 4, 5, 6, 7]
durations = [1, 2, 3, 100, 4, 5, 100]
max_duration = max(durations)
longest_events = (str(event) for event, duration in zip(events, durations)
                  if duration == max_duration)
print(f"The longest event time is {max_duration}, for the event(s): {','.join(longest_events)}")

Returning the index of max value in a list considering another list as a allowed index in python

Use the key argument for max:

max(a,key = lambda i: b[i]) #3

Getting the index of the returned max or min item using max()/min() on a list

if is_min_level:
    return values.index(min(values))
else:
    return values.index(max(values))

Python, finding the max value of an array above a specific value and it's index

We can find by:

• Finding list of indexes in sequence which are above threshold
• Finding max of values in these indexes

Code

import pandas as pd
import numpy as np

def find_max(a, lower_bound):
    ' Finds max above threshold '
    
    # Find indexes which are above threshold
    valid_idx = np.where(a >= lower_bound)[0]
    
    if valid_idx.size > 0:
        # Find maximum from these indexes
        max_idx = valid_idx[a[valid_idx].argmax()]
        return max_idx, a[max_idx]     # return index and max value

Test

data = [(1, 1), (2, 0), (10, 2), (5, 0)]
df = pd.DataFrame(data, columns  = ['a','b'])
print("DataFrame\n", df)
print()

# Find max in each column of DataFrame above lower bound
lower_bound = 8
for (column_name, column_data) in df.iteritems():
    found_max = find_max(column_data, lower_bound)
    if found_max:
        print(f'Column {column_name}: max index {found_max[0]}, max_value: {found_max[1]}')
    else:
        print(f'Column {column_name}: No max found')

Output

DataFrame
     a  b
0   1  1
1   2  0
2  10  2
3   5  0

Column a: max index 2, max_value: 10
Column b: No max found

How to find max value and its index in a row of 2d list?

as suggested in comments you can use max to get the max values from your list and argmax for getting the position.

np.argmax(q_table, axis=1) #returns list of position of max value in each list.

np.max(q_table, axis=1)  # return list of max value in each  list.

you can then use zip function to iterate both the list together and store the output in list of list

import numpy as np
max_list_with_position=[ [x,y] for x,y in zip(np.argmax(q_table, axis=1),np.max(q_table, axis=1))]
print(max_list_with_position)

output:

[[2, 0.61], [1, 0.79], [3, 0.93], [2, 0.61], [3, 0.69]]

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