104

I am facing a strange behavior of the round() function:

for i in range(1, 15, 2):
    n = i / 2
    print(n, "=>", round(n))

This code prints:

0.5 => 0
1.5 => 2
2.5 => 2
3.5 => 4
4.5 => 4
5.5 => 6
6.5 => 6

I expected the floating values to be always rounded up, but instead, it is rounded to the nearest even number.

Why such behavior, and what is the best way to get the correct result?

I tried to use the fractions but the result is the same.

martineau
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Delgan
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    can't explain the behaviour of `round()` but you could use `math.ceil()` if you always want to round up – yurib Oct 08 '15 at 15:16
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    @yurib I would like `1.3` to be rounded down to `1`, so I can not use `ceil()`. – Delgan Oct 08 '15 at 15:17
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    Possible duplicate of [Limiting floats to two decimal points](http://stackoverflow.com/questions/455612/limiting-floats-to-two-decimal-points) – yurib Oct 08 '15 at 15:19
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    Many days have passed since I studied error analysis. However If I recall correctly, the rounding of `5*10**-k` depends on the digit preceding it. By rounding up for uneven digits and down for even digits, you get a positive error half the time and an even error half the time (in theory). When you perform many additions, those errors can cancel each-other – StoryTeller - Unslander Monica Oct 08 '15 at 15:22

19 Answers19

83

The Numeric Types section documents this behaviour explicitly:

round(x[, n])
x rounded to n digits, rounding half to even. If n is omitted, it defaults to 0.

Note the rounding half to even. This is also called bankers rounding; instead of always rounding up or down (compounding rounding errors), by rounding to the nearest even number you average out rounding errors.

If you need more control over the rounding behaviour, use the decimal module, which lets you specify exactly what rounding strategy should be used.

For example, to round up from half:

>>> from decimal import localcontext, Decimal, ROUND_HALF_UP
>>> with localcontext() as ctx:
...     ctx.rounding = ROUND_HALF_UP
...     for i in range(1, 15, 2):
...         n = Decimal(i) / 2
...         print(n, '=>', n.to_integral_value())
...
0.5 => 1
1.5 => 2
2.5 => 3
3.5 => 4
4.5 => 5
5.5 => 6
6.5 => 7
Martijn Pieters
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    IEEE 754 rounding half to even is also described at https://en.wikipedia.org/wiki/Rounding#Round_half_to_even – Robert E Oct 08 '15 at 15:54
  • In your example, is there a benefit to modifying the local context as opposed to just using the `rounding` argument as in: `n.to_integral_value(rounding=ROUND_HALF_UP)`? – dhobbs Mar 16 '19 at 04:45
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    @dhobbs: setting the context once is clearer in intent, but from a technical point of view there is no difference. – Martijn Pieters Mar 16 '19 at 14:14
44

For example:

from decimal import Decimal, ROUND_HALF_UP

Decimal(1.5).quantize(0, ROUND_HALF_UP)

# This also works for rounding to the integer part:
Decimal(1.5).to_integral_value(rounding=ROUND_HALF_UP)
dhobbs
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29

You can use this:

import math
def normal_round(n):
    if n - math.floor(n) < 0.5:
        return math.floor(n)
    return math.ceil(n)

It will round number up or down properly.

fedor2612
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    Time and time I am shocked there is not internal function like this. I mean, it is not like people nowadays use a lot of numpy and math in python to implement numerical algorithms.... – lalala Jan 06 '21 at 09:11
  • It does round 'up or down', but unfortunately doesn't work with negative numbers. – drws Oct 06 '21 at 17:04
25

round() will round either up or down, depending on if the number is even or odd. A simple way to only round up is:

int(num + 0.5)

If you want this to work properly for negative numbers use:

((num > 0) - (num < 0)) * int(abs(num) + 0.5)

Note, this can mess up for large numbers or really precise numbers like 5000000000000001.0 and 0.49999999999999994.

Matthew D. Scholefield
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    There are some subtleties that aren't addressed by this solution. E.g., what result does this give if `num = -2.4`? What about `num = 0.49999999999999994`? `num = 5000000000000001.0`? On a typical machine using IEEE 754 format and semantics, this solution gives the wrong answer for all three of these cases. – Mark Dickinson Apr 10 '18 at 11:37
  • @Mark Dickinson I've updated the post to mention this. Thanks – Matthew D. Scholefield Apr 10 '18 at 16:10
  • Strictly speaking, both 0.49999999999999994 and 5000000000000001.0 are problematic due to precision. In both cases, adding 0.5 causes necessary precision bits to "fall off" the right hand side of the IEEE 754 double (64bit) mantissa (52 fraction bits + implicit 1.0). The first case basically doubles the value, pushing the (set) LSB out, while the second case is so large that the 0.5 is smaller than the existing LSB value. In fact, for 2^52 <= num < 2^53, it will round integers to even (prob. due to math chip rounding 80bit internal back to 64bit output). num >= 2^53 adding 0.5 does nothing. – Uber Kluger Oct 23 '21 at 09:31
8

The behavior you are seeing is typical IEEE 754 rounding behavior. If it has to choose between two numbers that are equally different from the input, it always picks the even one. The advantage of this behavior is that the average rounding effect is zero - equally many numbers round up and down. If you round the half way numbers in a consistent direction the rounding will affect the expected value.

The behavior you are seeing is correct if the objective is fair rounding, but that is not always what is needed.

One trick to get the type of rounding you want is to add 0.5 and then take the floor. For example, adding 0.5 to 2.5 gives 3, with floor 3.

Patricia Shanahan
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8

Love the fedor2612 answer. I expanded it with an optional "decimals" argument for those who want to use this function to round any number of decimals (say for example if you want to round a currency $26.455 to $26.46).

import math

def normal_round(n, decimals=0):
    expoN = n * 10 ** decimals
    if abs(expoN) - abs(math.floor(expoN)) < 0.5:
        return math.floor(expoN) / 10 ** decimals
    return math.ceil(expoN) / 10 ** decimals

oldRounding = round(26.455,2)
newRounding = normal_round(26.455,2)

print(oldRounding)
print(newRounding)

Output:

26.45

26.46

Community
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Joe Cat
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  • Great function! Never thought I'll face such an issue with rounding 133.125 with 2 digits to 133.13 nor to 133.12 . Thanks, Man! – akushyn Dec 03 '21 at 21:44
6

Why make it so complicated?

def HalfRoundUp(value):
    return int(value + 0.5)

You could of course make it into a lambda which would be:

HalfRoundUp = lambda value: int(value + 0.5)
TeaCoast
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4

Short version: use the decimal module. It can represent numbers like 2.675 precisely, unlike Python floats where 2.675 is really 2.67499999999999982236431605997495353221893310546875 (exactly). And you can specify the rounding you desire: ROUND_CEILING, ROUND_DOWN, ROUND_FLOOR, ROUND_HALF_DOWN, ROUND_HALF_EVEN, ROUND_HALF_UP, ROUND_UP, and ROUND_05UP are all options.

rmunn
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2

Rounding to the nearest even number has become common practice in numerical disciplines. "Rounding up" produces a slight bias towards larger results.

So, from the perspective of the scientific establishment, round has the correct behavior.

MRocklin
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  • Sure, it's the correct way if you are processing measured data, running simulations etc. But it's incorrect, for example, if you would like to calculate grades in school. In Hungary, we have a 5-grade grading system, and an average of 4.5 is rounded up to 5. I used this as an example when teaching my son Python, and I was stunned when round(4.5) gave 5. I had a hard time explaining to him why Python rounding works differently from what he learned in school about rounding... – kol Feb 04 '21 at 09:27
1

Here is another solution. It will work as normal rounding in excel.

from decimal import Decimal, getcontext, ROUND_HALF_UP

round_context = getcontext()
round_context.rounding = ROUND_HALF_UP

def c_round(x, digits, precision=5):
    tmp = round(Decimal(x), precision)
    return float(tmp.__round__(digits))

c_round(0.15, 1) -> 0.2, c_round(0.5, 0) -> 1

discover
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  • Anyone wondering about tmp.__round__, see [Python built-in function source code - round()](https://stackoverflow.com/questions/46078627/python-built-in-function-source-code-round) or [Python 3 Decimal rounding half down with ROUND_HALF_UP context](https://stackoverflow.com/questions/40631553/python-3-decimal-rounding-half-down-with-round-half-up-context). – Uber Kluger Oct 23 '21 at 20:39
1

The following solution achieved "school fashion rounding" without using the decimal module (which turns out to be slow).

def school_round(a_in,n_in):
''' python uses "banking round; while this round 0.05 up" '''
    if (a_in * 10 ** (n_in + 1)) % 10 == 5:
        return round(a_in + 1 / 10 ** (n_in + 1), n_in)
    else:
        return round(a_in, n_in)

e.g.

print(round(0.005,2)) # 0
print(school_round(0.005,2)) #0.01
1

In the question this is basically an issue when dividing a positive integer by 2. The easisest way is int(n + 0.5) for individual numbers.

However we cannot apply this to series, therefore what we then can do for example for a pandas dataframe, and without going into loops, is:

import numpy as np
df['rounded_division'] = np.where(df['some_integer'] % 2 == 0, round(df['some_integer']/2,0), round((df['some_integer']+1)/2,0))
Gursel Karacor
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1

So just to make sure there is a crystal clear working example here, I wrote a small convenience function

def round_half_up(x: float, num_decimals: int) -> float:
    """Use explicit ROUND HALF UP. See references, for an explanation.

    This is the proper way to round, as taught in school.

    Args:
        x:
        num_decimals:

    Returns:
            https://stackoverflow.com/questions/33019698/how-to-properly-round-up-half-float-numbers-in-python

    """

    if num_decimals < 0:
        raise ValueError("Num decimals needs to be at least 0.")
    target_precision = "1." + "0" * num_decimals
    rounded_x = float(Decimal(x).quantize(Decimal(target_precision), ROUND_HALF_UP))
    return rounded_x

And an appropriate set of test cases

def test_round_half_up():
    x = 1.5
    y = round_half_up(x, 0)
    assert y == 2.0

    y = round_half_up(x, 1)
    assert y == 1.5

    x = 1.25
    y = round_half_up(x, 1)
    assert y == 1.3

    y = round_half_up(x, 2)
    assert y == 1.25

1

A small addition as the rounding half up with some of the solutions might not work as expected in some cases.

Using the function from above for instance:

from decimal import Decimal, ROUND_HALF_UP
def round_half_up(x: float, num_decimals: int) -> float:
    if num_decimals < 0:
        raise ValueError("Num decimals needs to be at least 0.")
    target_precision = "1." + "0" * num_decimals
    rounded_x = float(Decimal(x).quantize(Decimal(target_precision), ROUND_HALF_UP))
    return rounded_x
round_half_up(1.35, 1)
1.4
round_half_up(4.35, 1)
4.3

Where I was expecting 4.4. What did the trick for me was converting x into a string first.

from decimal import Decimal, ROUND_HALF_UP
def round_half_up(x: float, num_decimals: int) -> float:
    if num_decimals < 0:
        raise ValueError("Num decimals needs to be at least 0.")
    target_precision = "1." + "0" * num_decimals
    rounded_x = float(Decimal(str(x)).quantize(Decimal(target_precision), ROUND_HALF_UP))
    return rounded_x

round_half_up(4.35, 1)
4.4
dodge
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0

You can use:

from decimal import Decimal, ROUND_HALF_UP

for i in range(1, 15, 2):
    n = i / 2
    print(n, "=>", Decimal(str(n)).quantize(Decimal("1"), rounding=ROUND_HALF_UP))
cdonts
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0

A classical mathematical rounding without any libraries

def rd(x,y=0):
''' A classical mathematical rounding by Voznica '''
m = int('1'+'0'*y) # multiplier - how many positions to the right
q = x*m # shift to the right by multiplier
c = int(q) # new number
i = int( (q-c)*10 ) # indicator number on the right
if i >= 5:
    c += 1
return c/m

Compare:

print( round(0.49), round(0.51), round(0.5), round(1.5), round(2.5), round(0.15,1))  # 0  1  0  2  2  0.1

print( rd(0.49), rd(0.51), rd(0.5), rd(1.5), rd(2.5), rd(0.15,1))  # 0  1  1  2  3  0.2
0

Knowing that round(9.99,0) rounds to int=10 and int(9.99) rounds to int=9 brings success:

Goal: Provide lower and higher round number depending on value

    def get_half_round_numers(self, value):
        """
        Returns dict with upper_half_rn and lower_half_rn
        :param value:
        :return:
        """
        hrns = {}
        if not isinstance(value, float):
            print("Error>Input is not a float. None return.")
            return None

        value = round(value,2)
        whole = int(value) # Rounds 9.99 to 9
        remainder = (value - whole) * 100

        if remainder >= 51:
            hrns['upper_half_rn'] = round(round(value,0),2)  # Rounds 9.99 to 10
            hrns['lower_half_rn'] = round(round(value,0) - 0.5,2)
        else:
            hrns['lower_half_rn'] = round(int(value),2)
            hrns['upper_half_rn'] = round(int(value) + 0.5,2)

        return hrns

Some testing:

enter image description here

yw

gies0r
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0
import math
# round tossing n digits from the end
def my_round(n, toss=1):

    def normal_round(n):
        if isinstance(n, int):
            return n
        intn, dec = str(n).split(".")
        if int(dec[-1]) >= 5:
            if len(dec) == 1:
                return math.ceil(n)
            else:
                return float(intn + "." + str(int(dec[:-1]) + 1))
        else:
            return float(intn + "." + dec[:-1])

    while toss >= 1:
        n = normal_round(n)
        toss -= 1
    return n


for n in [1.25, 7.3576, 30.56]:
    print(my_round(n, 2))

1.0
7.36
31
LetzerWille
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-1

You can try this

def round(num):
    return round(num + 10**(-9))

it will work since num = x.5 will always will be x.5 + 0.00...01 in the process which its closer to x+1 hence the round function will work properly and it will round x.5 to x+1

seVenVo1d
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  • Now `x.499999999` will be subject to half-even rounding, and will (half the time, assuming floating point precision issues don't force it one way or the other) get rounded up. That's worse than the initial scenario, as you're now rounding to the more distant number. – ShadowRanger Aug 19 '19 at 17:21