I feel compelled to provide a counterpoint to Ashwini Chaudhary's answer. Despite appearances, the two-argument form of the round function does not round a Python float to a given number of decimal places, and it's often not the solution you want, even when you think it is. Let me explain...

The ability to round a (Python) float to some number of decimal places is something that's frequently requested, but turns out to be rarely what's actually needed. The beguilingly simple answer round(x, number_of_places) is something of an attractive nuisance: it looks as though it does what you want, but thanks to the fact that Python floats are stored internally in binary, it's doing something rather subtler. Consider the following example:

>>> round(52.15, 1)
52.1

With a naive understanding of what round does, this looks wrong: surely it should be rounding up to 52.2 rather than down to 52.1? To understand why such behaviours can't be relied upon, you need to appreciate that while this looks like a simple decimal-to-decimal operation, it's far from simple.

So here's what's really happening in the example above. (deep breath) We're displaying a decimal representation of the nearest binary floating-point number to the nearest n-digits-after-the-point decimal number to a binary floating-point approximation of a numeric literal written in decimal. So to get from the original numeric literal to the displayed output, the underlying machinery has made four separate conversions between binary and decimal formats, two in each direction. Breaking it down (and with the usual disclaimers about assuming IEEE 754 binary64 format, round-ties-to-even rounding, and IEEE 754 rules):

  1. First the numeric literal 52.15 gets parsed and converted to a Python float. The actual number stored is 7339460017730355 * 2**-47, or 52.14999999999999857891452847979962825775146484375.

  2. Internally as the first step of the round operation, Python computes the closest 1-digit-after-the-point decimal string to the stored number. Since that stored number is a touch under the original value of 52.15, we end up rounding down and getting a string 52.1. This explains why we're getting 52.1 as the final output instead of 52.2.

  3. Then in the second step of the round operation, Python turns that string back into a float, getting the closest binary floating-point number to 52.1, which is now 7332423143312589 * 2**-47, or 52.10000000000000142108547152020037174224853515625.

  4. Finally, as part of Python's read-eval-print loop (REPL), the floating-point value is displayed (in decimal). That involves converting the binary value back to a decimal string, getting 52.1 as the final output.

In Python 2.7 and later, we have the pleasant situation that the two conversions in step 3 and 4 cancel each other out. That's due to Python's choice of repr implementation, which produces the shortest decimal value guaranteed to round correctly to the actual float. One consequence of that choice is that if you start with any (not too large, not too small) decimal literal with 15 or fewer significant digits then the corresponding float will be displayed showing those exact same digits:

>>> x = 15.34509809234
>>> x
15.34509809234

Unfortunately, this furthers the illusion that Python is storing values in decimal. Not so in Python 2.6, though! Here's the original example executed in Python 2.6:

>>> round(52.15, 1)
52.200000000000003

Not only do we round in the opposite direction, getting 52.2 instead of 52.1, but the displayed value doesn't even print as 52.2! This behaviour has caused numerous reports to the Python bug tracker along the lines of "round is broken!". But it's not round that's broken, it's user expectations. (Okay, okay, round is a little bit broken in Python 2.6, in that it doesn't use correct rounding.)

Short version: if you're using two-argument round, and you're expecting predictable behaviour from a binary approximation to a decimal round of a binary approximation to a decimal halfway case, you're asking for trouble.

So enough with the "two-argument round is bad" argument. What should you be using instead? There are a few possibilities, depending on what you're trying to do.

  • If you're rounding for display purposes, then you don't want a float result at all; you want a string. In that case the answer is to use string formatting:

    >>> format(66.66666666666, '.4f')
    '66.6667'
    >>> format(1.29578293, '.6f')
    '1.295783'
    

    Even then, one has to be aware of the internal binary representation in order not to be surprised by the behaviour of apparent decimal halfway cases.

    >>> format(52.15, '.1f')
    '52.1'
    
  • If you're operating in a context where it matters which direction decimal halfway cases are rounded (for example, in some financial contexts), you might want to represent your numbers using the Decimal type. Doing a decimal round on the Decimal type makes a lot more sense than on a binary type (equally, rounding to a fixed number of binary places makes perfect sense on a binary type). Moreover, the decimal module gives you better control of the rounding mode. In Python 3, round does the job directly. In Python 2, you need the quantize method.

    >>> Decimal('66.66666666666').quantize(Decimal('1e-4'))
    Decimal('66.6667')
    >>> Decimal('1.29578293').quantize(Decimal('1e-6'))
    Decimal('1.295783')
    
  • In rare cases, the two-argument version of round really is what you want: perhaps you're binning floats into bins of size 0.01, and you don't particularly care which way border cases go. However, these cases are rare, and it's difficult to justify the existence of the two-argument version of the round builtin based on those cases alone.

Answer from Mark Dickinson on Stack Overflow
Top answer
1 of 6
207

I feel compelled to provide a counterpoint to Ashwini Chaudhary's answer. Despite appearances, the two-argument form of the round function does not round a Python float to a given number of decimal places, and it's often not the solution you want, even when you think it is. Let me explain...

The ability to round a (Python) float to some number of decimal places is something that's frequently requested, but turns out to be rarely what's actually needed. The beguilingly simple answer round(x, number_of_places) is something of an attractive nuisance: it looks as though it does what you want, but thanks to the fact that Python floats are stored internally in binary, it's doing something rather subtler. Consider the following example:

>>> round(52.15, 1)
52.1

With a naive understanding of what round does, this looks wrong: surely it should be rounding up to 52.2 rather than down to 52.1? To understand why such behaviours can't be relied upon, you need to appreciate that while this looks like a simple decimal-to-decimal operation, it's far from simple.

So here's what's really happening in the example above. (deep breath) We're displaying a decimal representation of the nearest binary floating-point number to the nearest n-digits-after-the-point decimal number to a binary floating-point approximation of a numeric literal written in decimal. So to get from the original numeric literal to the displayed output, the underlying machinery has made four separate conversions between binary and decimal formats, two in each direction. Breaking it down (and with the usual disclaimers about assuming IEEE 754 binary64 format, round-ties-to-even rounding, and IEEE 754 rules):

  1. First the numeric literal 52.15 gets parsed and converted to a Python float. The actual number stored is 7339460017730355 * 2**-47, or 52.14999999999999857891452847979962825775146484375.

  2. Internally as the first step of the round operation, Python computes the closest 1-digit-after-the-point decimal string to the stored number. Since that stored number is a touch under the original value of 52.15, we end up rounding down and getting a string 52.1. This explains why we're getting 52.1 as the final output instead of 52.2.

  3. Then in the second step of the round operation, Python turns that string back into a float, getting the closest binary floating-point number to 52.1, which is now 7332423143312589 * 2**-47, or 52.10000000000000142108547152020037174224853515625.

  4. Finally, as part of Python's read-eval-print loop (REPL), the floating-point value is displayed (in decimal). That involves converting the binary value back to a decimal string, getting 52.1 as the final output.

In Python 2.7 and later, we have the pleasant situation that the two conversions in step 3 and 4 cancel each other out. That's due to Python's choice of repr implementation, which produces the shortest decimal value guaranteed to round correctly to the actual float. One consequence of that choice is that if you start with any (not too large, not too small) decimal literal with 15 or fewer significant digits then the corresponding float will be displayed showing those exact same digits:

>>> x = 15.34509809234
>>> x
15.34509809234

Unfortunately, this furthers the illusion that Python is storing values in decimal. Not so in Python 2.6, though! Here's the original example executed in Python 2.6:

>>> round(52.15, 1)
52.200000000000003

Not only do we round in the opposite direction, getting 52.2 instead of 52.1, but the displayed value doesn't even print as 52.2! This behaviour has caused numerous reports to the Python bug tracker along the lines of "round is broken!". But it's not round that's broken, it's user expectations. (Okay, okay, round is a little bit broken in Python 2.6, in that it doesn't use correct rounding.)

Short version: if you're using two-argument round, and you're expecting predictable behaviour from a binary approximation to a decimal round of a binary approximation to a decimal halfway case, you're asking for trouble.

So enough with the "two-argument round is bad" argument. What should you be using instead? There are a few possibilities, depending on what you're trying to do.

  • If you're rounding for display purposes, then you don't want a float result at all; you want a string. In that case the answer is to use string formatting:

    >>> format(66.66666666666, '.4f')
    '66.6667'
    >>> format(1.29578293, '.6f')
    '1.295783'
    

    Even then, one has to be aware of the internal binary representation in order not to be surprised by the behaviour of apparent decimal halfway cases.

    >>> format(52.15, '.1f')
    '52.1'
    
  • If you're operating in a context where it matters which direction decimal halfway cases are rounded (for example, in some financial contexts), you might want to represent your numbers using the Decimal type. Doing a decimal round on the Decimal type makes a lot more sense than on a binary type (equally, rounding to a fixed number of binary places makes perfect sense on a binary type). Moreover, the decimal module gives you better control of the rounding mode. In Python 3, round does the job directly. In Python 2, you need the quantize method.

    >>> Decimal('66.66666666666').quantize(Decimal('1e-4'))
    Decimal('66.6667')
    >>> Decimal('1.29578293').quantize(Decimal('1e-6'))
    Decimal('1.295783')
    
  • In rare cases, the two-argument version of round really is what you want: perhaps you're binning floats into bins of size 0.01, and you don't particularly care which way border cases go. However, these cases are rare, and it's difficult to justify the existence of the two-argument version of the round builtin based on those cases alone.

2 of 6
115

Use the built-in function round():

In [23]: round(66.66666666666,4)
Out[23]: 66.6667

In [24]: round(1.29578293,6)
Out[24]: 1.295783

help on round():

round(number[, ndigits]) -> floating point number

Round a number to a given precision in decimal digits (default 0 digits). This always returns a floating point number. Precision may be negative.

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W3Schools
w3schools.com › python › ref_func_round.asp
Python round() Function
Python Examples Python Compiler ... Python Training ... The round() function returns a floating point number that is a rounded version of the specified number, with the specified number of decimals....
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Mimo
mimo.org › glossary › python › round-function
Python round(): Rounding Numbers in Python
The Python round() function rounds floating-point numbers to a specified number of decimal places.
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DataCamp
datacamp.com › tutorial › python-round-to-two-decimal-places
Round to 2 Decimal Places in Python: round(), f-strings & More | DataCamp
June 2, 2026 - The round() function is Python’s built-in function for rounding floating-point numbers to the specified number of decimal places. You can specify the number of decimal places to round by providing a value in the second argument.
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Python documentation
docs.python.org › 3 › tutorial › floatingpoint.html
15. Floating-Point Arithmetic: Issues and Limitations — Python 3.14.7 documentation
Instead of displaying the full decimal value, many languages (including older versions of Python), round the result to 17 significant digits: ... >>> from decimal import Decimal >>> from fractions import Fraction >>> Fraction.from_float(0.1) Fraction(3602879701896397, 36028797018963968) >>> (0.1).as_integer_ratio() (3602879701896397, 36028797018963968) >>> Decimal.from_float(0.1) Decimal('0.1000000000000000055511151231257827021181583404541015625') >>> format(Decimal.from_float(0.1), '.17') '0.10000000000000001'
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Python
docs.python.org › 3 › library › decimal.html
decimal — Decimal fixed-point and floating-point arithmetic
Source code: Lib/decimal.py The decimal module provides support for fast correctly rounded decimal floating-point arithmetic. It offers several advantages over the float datatype: Decimal “is based...
Find elsewhere
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GeeksforGeeks
geeksforgeeks.org › python › round-function-python
round() function in Python - GeeksforGeeks
Return: Returns a rounded int or float. When the second parameter (ndigits) is not provided, round() automatically rounds the number to the nearest integer. If the number is already an integer, it remains unchanged. For decimal numbers, Python rounds to the closest integer using its standard rounding rule.
Published: March 20, 2026
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Analytics Vidhya
analyticsvidhya.com › home › 6 ways to round floating value to two decimals in python
6 Ways to Round Floating Value to Two Decimals in Python
November 4, 2024 - However, modern formatting methods ... format a floating-point number with two decimal places in Python, you can use the .2f format specifier....
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Server Academy
serveracademy.com › blog › python-round-function-tutorial
Python Round() Function Tutorial Blog | Server Academy
November 14, 2024 - Rounding numbers is a common operation in Python, especially when working with floating point numbers. Python’s function makes it easy to round numbers to a sp…
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Programiz
programiz.com › python-programming › methods › built-in › round
Python round()
from decimal import Decimal # normal float num = 2.675 · print(round(num, 2)) # using decimal.Decimal (passed float as string for precision) num = Decimal('2.675')
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Reddit
reddit.com › r/learnpython › rounding and float point precision
r/learnpython on Reddit: Rounding and float point precision
June 12, 2025 -

Hello all

Not an expert coder, but I can usually pick things up in Python. However, I found something that stumped me and hoping I can get some help.

I have a pandas data frame. In that df, I have several columns of floats. For each column, each entry is a product of given values, those given values extend to the hundredths place. Once the product is calculated, I round the product to two decimal places.

Finally, for each row, I sum up the values in each column to get a total. That total is rounded to the nearest integer. For the purpose of this project, the rounding rules I want to follow are “round-to-even.”

My understanding is that the round() function in Python defaults to the “round-to-even” rule, which is exactly what I need.

However, I saw that before rounding, one of my totals was 195.50 (after summing up the corresponding products for that row). So the round() function should have rounded this value to 196 according to “round-to-even” rules. But it actually output 195.

When I was doing some digging, I found that sometimes decimals have precision error because the decimal portion can’t be captured in binary notation. And that could be why the round() function inappropriately rounded to 195 instead of 196.

Now, I get the “big picture” of this, but I feel I am missing some critical details my understanding is that integers can always be repped as sums of powers of 2. But not all decimals can be. For example 0.1 is not the sum of powers of 2. In these situations, the decimal portion is basically approximated by a fraction and this approximation is what could lead to 0.1 really being 0.10000000000001 or something similar.

However, my understanding is that decimals that terminate with a 5 are possible to represent in binary. Thus the precision error shouldn’t apply and the round() function should appropriately round.

What am I missing? Any help is greatly appreciated

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freeCodeCamp
freecodecamp.org › news › how-to-round-numbers-up-or-down-in-python
Python Round to Int – How to Round Up or Round Down to the Nearest Whole Number
May 24, 2022 - We'll then talk about the math.ceil() and math.floor() methods which rounds up and rounds down a number to the nearest whole number/integer respectively. These two methods are from the built-in math module in Python.
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AskPython
askpython.com › home › using python round()
Using Python round() - AskPython
August 6, 2022 - print(round(123.456, 0)) print(round(123.456, -1)) print(round(123.456, -2)) print(round(123.456, -3)) ... Since floating-point numbers are defined by their precision, Python approximates these numbers during calculations.
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Guru99
guru99.com › home › python › python round() function with examples
Python round() Function with EXAMPLES
July 10, 2026 - Python round() is a built-in function that returns a floating-point or integer value rounded to a specified number of decimal places, using banker’s rounding to break ties toward the nearest even digit.
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GeeksforGeeks
geeksforgeeks.org › numpy › numpy-round_-python
numpy.round_() in Python - GeeksforGeeks
December 6, 2024 - The round_() function in NumPy rounds the elements of an array to a specified number of decimal places. This function is extremely useful when working with floating-point numbers and when precision is important in scientific computing or data ...
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BitDegree
bitdegree.org › learn › python-round
Python Round() Explained: Syntax, Arguments, Usage
February 13, 2020 - Learn to code basic programming easily. Discover popular programming languages & learn computer programming. Learn to code with real examples.
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Tanner Dolby
tannerdolby.com › writing › rounding-in-python
Rounding floating point numbers with Python
July 13, 2021 - # Arithmetic operations (where precision and rounding come into play) val = Decimal(5.05362) + Decimal(2.61589) print(val) # 7.66951 # Change rounding in context to round up (from default ROUND_HALF_EVEN) ctx.rounding = ROUND_DOWN val = Decimal(5.05362) + Decimal(2.61589) print(val) # 7.66950 · There is much more to be discovered in the decimal module, but I will leave that up to you. I hope this article shed some light on floating point numbers in Python and the options you have for dealing with extremely precise decimal calculations.
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Note.nkmk.me
note.nkmk.me › home › python
Round Numbers in Python: round(), Decimal.quantize() | note
January 15, 2024 - Built-in Functions - round() — ... ndigits. For floating point numbers (float), if the second argument is omitted, round() rounds to and returns an integer (int)....
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Updategadh
updategadh.com › home › python interview question › how to round numbers in python
How to Round Numbers in Python
February 6, 2025 - Python provides a built-in round() function that is used to round off a number to a specified number of decimal places. This function takes two arguments: the first is number, and the second is ndigits.
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Instagram
instagram.com › popular › round-float-python
Round Float Python
March 23, 2026 - Welcome back to Instagram. Sign in to see what your friends, family and interests have been capturing and sharing around the world.