Use max with axis=1: df = df.max(axis=1) print (df) 0 2.0 1 3.2 2 8.8 3 7.8 dtype: float64 And if need new column: df[‘max_value’] = df.max(axis=1) print (df) a b c max_value 0 1.2 2.0 0.10 2.0 1 2.1 1.1 3.20 3.2 2 0.2 1.9 8.80 8.8 3 3.3 7.8 0.12 7.8
What about max() highest = max(1, 2, 3) # or max([1, 2, 3]) for lists
Usually, you could just use max(nums) If you explicitly want to use a loop, try: max_value = None for n in nums: if max_value is None or n > max_value: max_value = n
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You can determine the maxval with max: maxval = max(my_list) Then get the indices using enumerate and a list comprehension: indices = [index for index, val in enumerate(my_list) if val == maxval] For your example, I get maxval == 58 indices = [5, 10, 11] As per Keyser’s suggestion, you could save iterating over the … Read more
heapq.nlargest: >>> import heapq, random >>> heapq.nlargest(3, (random.gauss(0, 1) for _ in xrange(100))) [1.9730767232998481, 1.9326532289091407, 1.7762926716966254]
Math.max only takes two arguments. If you want the maximum of three, use Math.max(MY_INT1, Math.max(MY_INT2, MY_DOUBLE2)).
>>> frame[‘HighScore’] = frame[[‘test1′,’test2′,’test3’]].max(axis=1) >>> frame name test1 test2 test3 HighScore 0 bill 85 35 51 85 1 joe 75 45 61 75 2 steve 85 83 45 85
Here’s one way to get the min and max values: $min = min(array_column($array, ‘Price’)); $max = max(array_column($array, ‘Price’)); To return the nested array for the min and max: $prices = array_column($array, ‘Price’); $min_array = $array[array_search(min($prices), $prices)]; $max_array = $array[array_search(max($prices), $prices)]; You could do each in one line since that looked like what you were trying … Read more
If you do not want to create a wrapper type you can use the ordered_float or ord_subset crate. For example extern crate ordered_float; extern crate ord_subset; #[test] fn test_example_() { use ordered_float::OrderedFloat; // OrderedFloat -> NaN is greater than all other values and equal to itself. // NotNaN -> NotNaN::new panics if called with NaN. … Read more