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Rounding a float number in python

I have a float numer
a = 1.263597
I hope get
b = 1.2635
But when I try
round (a,4)
then result is
1.2636
What should I do?

Try math.floor with this small modification -
import math
def floor_rounded(n,d):
return math.floor(n*10**d)/10**d
n = 1.263597
d = 4
output = floor_rounded(n,d)
print(output)
1.2635
For your example, you can just do math.floor(1.263597 * 10000)/10000
EDIT: Based on the valid comment by #Mark, here is another way of solving this, but this time forcing the custom rounding using string operations.
#EDIT: Alternate approach, based on the comment by Mark Dickinson
def string_rounded(n,d):
i,j = str(n).split('.')
return float(i+'.'+j[:d])
n = 8.04
d = 2
output = string_rounded(n,d)
output
8.04

Plain Python without importing any libraries (even not standard libraries):
def round_down(number, ndigits=None):
if ndigits is None or ndigits == 0:
# Return an integer if ndigits is 0
return int(number)
else:
return int(number * 10**ndigits) / 10**ndigits
a = 1.263597
b = round_down(a, 4)
print(b)
1.2635
Note that this function rounds towards zero, i.e. it rounds down positive floats and rounds up negative floats.

def round_down(number, ndigits=0):
return round(number-0.5/pow(10, ndigits), ndigits)
Run:
round_down(1.263597, 4)
>> 1.2635

Python: How to round numbers smaller than 1 adaptively with specified precision?

I usually use
x = round(x, 3)
to round a number to the precision of 3 digits. Now I have this array:
[-1.10882605e-04 -2.01874994e-05 3.24209095e-05 -1.56917988e-05
-4.61406358e-05 1.99080610e-05 7.04079594e-05 2.64600122e-05
-3.53022316e-05 1.50542793e-05]
And using the same code just flattens everything down to 0. What I would like to have though is a function that gives me the most significant 3 digits rounded like it usually works for numbers larger than 1. Like this:
special_round(0.00034567, 3)
=
0.000346
Any idea how this could be done? Thanks!

Here is a solution that figures out the order of magnitude and does an elment wise rounding.
Note that this will only work correctly for values < 1 and > -1, which I guess is a valid assumption regarding your example data.
import numpy as np
a = np.array([-1.10882605e-04, -2.01874994e-05, 3.24209095e-05, -1.56917988e-05,
-4.61406358e-05, 1.99080610e-05, 7.04079594e-05 , 2.64600122e-05,
-3.53022316e-05 , 1.50542793e-05])
def special_round(vec):
exponents = np.floor(np.log10(np.abs(vec))).astype(int)
return np.stack([np.round(v, decimals=-e+3) for v, e in zip(vec, exponents)])
b = special_round(a)
>>> array([-1.109e-04, -2.019e-05, 3.242e-05, -1.569e-05, -4.614e-05,
1.991e-05, 7.041e-05, 2.646e-05, -3.530e-05, 1.505e-05])

Problem is, numbers you provided are starting to be so small that you are approaching limit of floating point precision, thus some artifacts show up seemingly for no reason.
def special_round(number, precision):
negative = number < 0
number = abs(number)
i = 0
while number <= 1 or number >= 10:
if number <= 1:
i += 1
number *= 10
else:
i += -1
number /= 10
rounded = round(number, precision)
if negative:
rounded = -rounded
return rounded * (10 ** -i)
Output:
[-0.0001109, -2.019e-05, 3.2420000000000005e-05, -1.569e-05, -4.614e-05, 1.9910000000000004e-05, 7.041000000000001e-05, 2.646e-05, -3.5300000000000004e-05, 1.505e-05]

You can do so by creating a specific function using the math package:
from math import log10 , floor
import numpy as np
def round_it(x, sig):
return round(x, sig-int(floor(log10(abs(x))))-1)
a = np.array([-1.10882605e-04, -2.01874994e-05, 3.24209095e-05, -1.56917988e-05,
-4.61406358e-05, 1.99080610e-05, 7.04079594e-05, 2.64600122e-05,
-3.53022316e-05, 1.50542793e-05])
round_it_np = np.vectorize(round_it) # vectorize the function to apply on numpy array
round_it_np(a, 3) # 3 is rounding with 3 significant digits
This will result in
array([-1.11e-04, -2.02e-05, 3.24e-05, -1.57e-05, -4.61e-05, 1.99e-05,
7.04e-05, 2.65e-05, -3.53e-05, 1.51e-05])

Here is a solution:
from math import log10, ceil
def special_round(x, n) :
lx = log10(abs(x))
if lx >= 0 : return round(x, n)
return round(x, n-ceil(lx))
for x in [10.23456, 1.23456, 0.23456, 0.023456, 0.0023456] :
print (x, special_round(x, 3))
print (-x, special_round(-x, 3))
Output:
10.23456 10.235
-10.23456 -10.235
1.23456 1.235
-1.23456 -1.235
0.23456 0.235
-0.23456 -0.235
0.023456 0.0235
-0.023456 -0.0235
0.0023456 0.00235
-0.0023456 -0.00235

You can use the common logarithm (provided by the built-in math module) to calculate the position of the first significant digit in your number (with 2 representing the hundreds, 1 representing the tens, 0 representing the ones, -1 representing the 0.x, -2 representing the 0.0x and so on...). Knowing the position of the first significant digit, you can use it to properly round the number.
import math
def special_round(n, significant_digits=0):
first_significant_digit = math.ceil((math.log10(abs(n))))
round_digits = significant_digits - first_significant_digit
return round(n, round_digits)
>>> special_round(0.00034567, 3)
>>> 0.000346

Round to whole numbers without using conditional statements in Python - Logic

I'm taking a Python course at Udacity, and I'm trying to work this out for myself without looking at the answer. Perhaps you can give me a hint for my logic?
Below are the instructions and what I have so far. We haven't learned conditional statements yet, so I can't use those. We've only learned how to assign/print a variable, strings, indexing strings, sub-sequences, and .find. They just introduced the str command in this final exercise.
# Given a variable, x, that stores the
# value of any decimal number, write Python
# code that prints out the nearest whole
# number to x.
# If x is exactly half way between two
# whole numbers, round up, so
# 3.5 rounds to 4 and 2.5 rounds to 3.
# You may assume x is not negative.
# Hint: The str function can convert any number into a string.
# eg str(89) converts the number 89 to the string '89'
# Along with the str function, this problem can be solved
# using just the information introduced in unit 1.
# x = 3.14159
# >>> 3 (not 3.0)
# x = 27.63
# >>> 28 (not 28.0)
# x = 3.5
# >>> 4 (not 4.0)
x = 3.54159
#ENTER CODE BELOW HERE
x = str(x)
dec = x.find('.')
tenth = dec + 1
print x[0:dec]
////
So this gets me to print the characters up to the decimal point, but I can't figure out how to have the computer check whether "tenth" is > 4 or < 5 and print out something according to the answer.
I figured I could probably get far enough for it to return a -1 if "tenth" wasn't > 4, but I don't know how I can get it to print x[0:dec] if it's < 5 and x[0:dec]+1 if it's > 4.
:/
Could someone please give me a nudge in the right direction?

This is a weird restriction, but you could do this:
x = str(x)
dec_index = x.find('.')
tenth_index = dec_index + 1
tenth_place = x[tenth_index] # will be a string of length 1
should_round_up = 5 + tenth_place.find('5') + tenth_place.find('6') + tenth_place.find('7') + tenth_place.find('8') + tenth_place.find('9')
print int(x[0:dec_index]) + should_round_up
What we do is look at the tenths place. Since .find() returns -1 if the argument isn't found, the sum of the .find() calls will be -4 if if the tenths place is 5, 6, 7, 8, or 9 (since one of the .find() calls will succeed and return 0), but will be -5 if the tenths place is 0, 1, 2, 3, or 4. We add 5 to that, so that should_round_up equals 1 if we should round up, and 0 otherwise. Add that to the whole number part, and we're done.
That said, if you weren't subject to this artificial restriction, you would do:
print round(x)
And move on with your life.

judging by the accepted answer you only expects floats so that is pretty trivial to solve:
x = 3.54159
# split on .
a, b = str(x).split(".")
# cast left side to int and add result of test for right side being greater or equal to 5
print(int(a) + (int(b) >= 5))
(int(b) > 5) will be either 1 or 0 i.e True/False so we either add 1 when right side is > .5 or flooring when it's < .5 and adding 0.
If you were doing it mathematically you just need to print(int(x+.5)), anything >= .5 will mean x will be rounded up and floored when it is < .5.

x = 3.54159
# split on .
a, b = str(x).split(".")
# cast left side to int and add result of test for right side being greater or equal to 5
print(int(a) + (int(b[0]) >= 5))
# above code will not work with 3.14567 and the number with having two or more digits after decimal

I think it's easier...
x = x + 0.5
intPart, decPart = str(x).split(".")
print intPart
Examples:
If x = 1, then it will become 1.5 and intPart will be 1.
If x = 1.1, then it will become 1.6 and intPart will be 1.
If x = 1.6, then it will become 2.1 and intPart will be 2.
Note: it will only work for positive numbers.

This code will round numbers to the nearest whole
without using conditionals
You can do it this way
x = 3.54159
x = x + 0.5 # This automatically takes care of the rounding
str_x = str(x) # Converting number x to string
dp = str_x.find('.') # Finding decimal point index
print str_x[:dp] # Printing upto but excluding decimal point

I did the same course at Udacity. solved it using the following code:
y = str(x)
decimal = y.find('.')
y_increment = y[decimal+1:]
print decimal
print y_increment
# Section below finds >5
check5 = y_increment.find('5',0,1)
check6 = y_increment.find('6',0,1)
check7 = y_increment.find('7',0,1)
check8 = y_increment.find('8',0,1)
check9 = y_increment.find('9',0,1)
yes_increment = (check5 + 1) + (check6 + 1) + (check7 + 1) + (check8 + 1) + (check9 + 1)
print check5, check6, check7, check8, check9
#Calculate rounding up
z = x + (yes_increment)
z = str(z)
final_decimal = z.find('.')
print z[:final_decimal]

Python Decimal - engineering notation for mili (10e-3) and micro (10e-6)

Here is the example which is bothering me:
>>> x = decimal.Decimal('0.0001')
>>> print x.normalize()
>>> print x.normalize().to_eng_string()
0.0001
0.0001
Is there a way to have engineering notation for representing mili (10e-3) and micro (10e-6)?

Here's a function that does things explicitly, and also has support for using SI suffixes for the exponent:
def eng_string( x, format='%s', si=False):
'''
Returns float/int value <x> formatted in a simplified engineering format -
using an exponent that is a multiple of 3.
format: printf-style string used to format the value before the exponent.
si: if true, use SI suffix for exponent, e.g. k instead of e3, n instead of
e-9 etc.
E.g. with format='%.2f':
1.23e-08 => 12.30e-9
123 => 123.00
1230.0 => 1.23e3
-1230000.0 => -1.23e6
and with si=True:
1230.0 => 1.23k
-1230000.0 => -1.23M
'''
sign = ''
if x < 0:
x = -x
sign = '-'
exp = int( math.floor( math.log10( x)))
exp3 = exp - ( exp % 3)
x3 = x / ( 10 ** exp3)
if si and exp3 >= -24 and exp3 <= 24 and exp3 != 0:
exp3_text = 'yzafpnum kMGTPEZY'[ ( exp3 - (-24)) / 3]
elif exp3 == 0:
exp3_text = ''
else:
exp3_text = 'e%s' % exp3
return ( '%s'+format+'%s') % ( sign, x3, exp3_text)

EDIT:
Matplotlib implemented the engineering formatter, so one option is to directly use Matplotlibs formatter, e.g.:
import matplotlib as mpl
formatter = mpl.ticker.EngFormatter()
formatter(10000)
result: '10 k'
Original answer:
Based on Julian Smith's excellent answer (and this answer), I changed the function to improve on the following points:
Python3 compatible (integer division)
Compatible for 0 input
Rounding to significant number of digits, by default 3, no trailing zeros printed
so here's the updated function:
import math
def eng_string( x, sig_figs=3, si=True):
"""
Returns float/int value <x> formatted in a simplified engineering format -
using an exponent that is a multiple of 3.
sig_figs: number of significant figures
si: if true, use SI suffix for exponent, e.g. k instead of e3, n instead of
e-9 etc.
"""
x = float(x)
sign = ''
if x < 0:
x = -x
sign = '-'
if x == 0:
exp = 0
exp3 = 0
x3 = 0
else:
exp = int(math.floor(math.log10( x )))
exp3 = exp - ( exp % 3)
x3 = x / ( 10 ** exp3)
x3 = round( x3, -int( math.floor(math.log10( x3 )) - (sig_figs-1)) )
if x3 == int(x3): # prevent from displaying .0
x3 = int(x3)
if si and exp3 >= -24 and exp3 <= 24 and exp3 != 0:
exp3_text = 'yzafpnum kMGTPEZY'[ exp3 // 3 + 8]
elif exp3 == 0:
exp3_text = ''
else:
exp3_text = 'e%s' % exp3
return ( '%s%s%s') % ( sign, x3, exp3_text)

The decimal module is following the Decimal Arithmetic Specification, which states:
This is outdated - see below
to-scientific-string – conversion to numeric string
[...]
The coefficient is first converted to a string in base ten using the characters 0 through 9 with no leading zeros (except if its value is zero, in which case a single 0 character is used).
Next, the adjusted exponent is calculated; this is the exponent, plus the number of characters in the converted coefficient, less one. That is, exponent+(clength-1), where clength is the length of the coefficient in decimal digits.
If the exponent is less than or equal to zero and the adjusted exponent is greater than or equal to -6, the number will be converted
to a character form without using exponential notation.
[...]
to-engineering-string – conversion to numeric string
This operation converts a number to a string, using engineering
notation if an exponent is needed.
The conversion exactly follows the rules for conversion to scientific
numeric string except in the case of finite numbers where exponential
notation is used. In this case, the converted exponent is adjusted to be a multiple of three (engineering notation) by positioning the decimal point with one, two, or three characters preceding it (that is, the part before the decimal point will range from 1 through 999).
This may require the addition of either one or two trailing zeros.
If after the adjustment the decimal point would not be followed by a digit then it is not added. If the final exponent is zero then no indicator letter and exponent is suffixed.
Examples:
For each abstract representation [sign, coefficient, exponent] on the left, the resulting string is shown on the right.
Representation
String
[0,123,1]
"1.23E+3"
[0,123,3]
"123E+3"
[0,123,-10]
"12.3E-9"
[1,123,-12]
"-123E-12"
[0,7,-7]
"700E-9"
[0,7,1]
"70"
Or, in other words:
>>> for n in (10 ** e for e in range(-1, -8, -1)):
... d = Decimal(str(n))
... print d.to_eng_string()
...
0.1
0.01
0.001
0.0001
0.00001
0.000001
100E-9

I realize that this is an old thread, but it does come near the top of a search for python engineering notation and it seems prudent to have this information located here.
I am an engineer who likes the "engineering 101" engineering units. I don't even like designations such as 0.1uF, I want that to read 100nF. I played with the Decimal class and didn't really like its behavior over the range of possible values, so I rolled a package called engineering_notation that is pip-installable.
pip install engineering_notation
From within Python:
>>> from engineering_notation import EngNumber
>>> EngNumber('1000000')
1M
>>> EngNumber(1000000)
1M
>>> EngNumber(1000000.0)
1M
>>> EngNumber('0.1u')
100n
>>> EngNumber('1000m')
1
This package also supports comparisons and other simple numerical operations.
https://github.com/slightlynybbled/engineering_notation

The «full» quote shows what is wrong!
The decimal module is indeed following the proprietary (IBM) Decimal Arithmetic Specification.
Quoting this IBM specification in its entirety clearly shows what is wrong with decimal.to_eng_string() (emphasis added):
to-engineering-string – conversion to numeric string
This operation converts a number to a string, using engineering
notation if an exponent is needed.
The conversion exactly follows the rules for conversion to scientific
numeric string except in the case of finite numbers where exponential
notation is used. In this case, the converted exponent is adjusted to be a multiple of three (engineering notation) by positioning the decimal point with one, two, or three characters preceding it (that is, the part before the decimal point will range from 1 through 999). This may require the addition of either one or two trailing zeros.
If after the adjustment the decimal point would not be followed by a digit then it is not added. If the final exponent is zero then no indicator letter and exponent is suffixed.
This proprietary IBM specification actually admits to not applying the engineering notation for numbers with an infinite decimal representation, for which ordinary scientific notation is used instead! This is obviously incorrect behaviour for which a Python bug report was opened.
Solution
from math import floor, log10
def powerise10(x):
""" Returns x as a*10**b with 0 <= a < 10
"""
if x == 0: return 0,0
Neg = x < 0
if Neg: x = -x
a = 1.0 * x / 10**(floor(log10(x)))
b = int(floor(log10(x)))
if Neg: a = -a
return a,b
def eng(x):
"""Return a string representing x in an engineer friendly notation"""
a,b = powerise10(x)
if -3 < b < 3: return "%.4g" % x
a = a * 10**(b % 3)
b = b - b % 3
return "%.4gE%s" % (a,b)
Source: https://code.activestate.com/recipes/578238-engineering-notation/
Test result
>>> eng(0.0001)
100E-6

Like the answers above, but a bit more compact:
from math import log10, floor
def eng_format(x,precision=3):
"""Returns string in engineering format, i.e. 100.1e-3"""
x = float(x) # inplace copy
if x == 0:
a,b = 0,0
else:
sgn = 1.0 if x > 0 else -1.0
x = abs(x)
a = sgn * x / 10**(floor(log10(x)))
b = int(floor(log10(x)))
if -3 < b < 3:
return ("%." + str(precision) + "g") % x
else:
a = a * 10**(b % 3)
b = b - b % 3
return ("%." + str(precision) + "gE%s") % (a,b)
Trial:
In [10]: eng_format(-1.2345e-4,precision=5)
Out[10]: '-123.45E-6'

drop trailing zeros from decimal

I have a long list of Decimals and that I have to adjust by factors of 10, 100, 1000,..... 1000000 depending on certain conditions. When I multiply them there is sometimes a useless trailing zero (though not always) that I want to get rid of. For example...
from decimal import Decimal
# outputs 25.0, PROBLEM! I would like it to output 25
print Decimal('2.5') * 10
# outputs 2567.8000, PROBLEM! I would like it to output 2567.8
print Decimal('2.5678') * 1000
Is there a function that tells the decimal object to drop these insignificant zeros? The only way I can think of doing this is to convert to a string and replace them using regular expressions.
Should probably mention that I am using python 2.6.5
EDIT
senderle's fine answer made me realize that I occasionally get a number like 250.0 which when normalized produces 2.5E+2. I guess in these cases I could try to sort them out and convert to a int

You can use the normalize method to remove extra precision.
>>> print decimal.Decimal('5.500')
5.500
>>> print decimal.Decimal('5.500').normalize()
5.5
To avoid stripping zeros to the left of the decimal point, you could do this:
def normalize_fraction(d):
normalized = d.normalize()
sign, digits, exponent = normalized.as_tuple()
if exponent > 0:
return decimal.Decimal((sign, digits + (0,) * exponent, 0))
else:
return normalized
Or more compactly, using quantize as suggested by user7116:
def normalize_fraction(d):
normalized = d.normalize()
sign, digit, exponent = normalized.as_tuple()
return normalized if exponent <= 0 else normalized.quantize(1)
You could also use to_integral() as shown here but I think using as_tuple this way is more self-documenting.
I tested these both against a few cases; please leave a comment if you find something that doesn't work.
>>> normalize_fraction(decimal.Decimal('55.5'))
Decimal('55.5')
>>> normalize_fraction(decimal.Decimal('55.500'))
Decimal('55.5')
>>> normalize_fraction(decimal.Decimal('55500'))
Decimal('55500')
>>> normalize_fraction(decimal.Decimal('555E2'))
Decimal('55500')

There's probably a better way of doing this, but you could use .rstrip('0').rstrip('.') to achieve the result that you want.
Using your numbers as an example:
>>> s = str(Decimal('2.5') * 10)
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
25
>>> s = str(Decimal('2.5678') * 1000)
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
2567.8
And here's the fix for the problem that #gerrit pointed out in the comments:
>>> s = str(Decimal('1500'))
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
1500

Answer from the Decimal FAQ in the documentation:
>>> def remove_exponent(d):
... return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()
>>> remove_exponent(Decimal('5.00'))
Decimal('5')
>>> remove_exponent(Decimal('5.500'))
Decimal('5.5')
>>> remove_exponent(Decimal('5E+3'))
Decimal('5000')

Answer is mentioned in FAQ (https://docs.python.org/2/library/decimal.html#decimal-faq) but does not explain things.
To drop trailing zeros for fraction part you should use normalize:
>>> Decimal('100.2000').normalize()
Decimal('100.2')
>> Decimal('0.2000').normalize()
Decimal('0.2')
But this works different for numbers with leading zeros in sharp part:
>>> Decimal('100.0000').normalize()
Decimal('1E+2')
In this case we should use `to_integral':
>>> Decimal('100.000').to_integral()
Decimal('100')
So we could check if there's a fraction part:
>>> Decimal('100.2000') == Decimal('100.2000').to_integral()
False
>>> Decimal('100.0000') == Decimal('100.0000').to_integral()
True
And use appropriate method then:
def remove_exponent(num):
return num.to_integral() if num == num.to_integral() else num.normalize()
Try it:
>>> remove_exponent(Decimal('100.2000'))
Decimal('100.2')
>>> remove_exponent(Decimal('100.0000'))
Decimal('100')
>>> remove_exponent(Decimal('0.2000'))
Decimal('0.2')
Now we're done.

Use the format specifier %g. It seems remove to trailing zeros.
>>> "%g" % (Decimal('2.5') * 10)
'25'
>>> "%g" % (Decimal('2.5678') * 1000)
'2567.8'
It also works without the Decimal function
>>> "%g" % (2.5 * 10)
'25'
>>> "%g" % (2.5678 * 1000)
'2567.8'

I ended up doing this:
import decimal
def dropzeros(number):
mynum = decimal.Decimal(number).normalize()
# e.g 22000 --> Decimal('2.2E+4')
return mynum.__trunc__() if not mynum % 1 else float(mynum)
print dropzeros(22000.000)
22000
print dropzeros(2567.8000)
2567.8
note: casting the return value as a string will limit you to 12 significant digits

Slightly modified version of A-IV's answer
NOTE that Decimal('0.99999999999999999999999999995').normalize() will round to Decimal('1')
def trailing(s: str, char="0"):
return len(s) - len(s.rstrip(char))
def decimal_to_str(value: decimal.Decimal):
"""Convert decimal to str
* Uses exponential notation when there are more than 4 trailing zeros
* Handles decimal.InvalidOperation
"""
# to_integral_value() removes decimals
if value == value.to_integral_value():
try:
value = value.quantize(decimal.Decimal(1))
except decimal.InvalidOperation:
pass
uncast = str(value)
# use exponential notation if there are more that 4 zeros
return str(value.normalize()) if trailing(uncast) > 4 else uncast
else:
# normalize values with decimal places
return str(value.normalize())
# or str(value).rstrip('0') if rounding edgecases are a concern

You could use :g to achieve this:
'{:g}'.format(3.140)
gives
'3.14'

This should work:
'{:f}'.format(decimal.Decimal('2.5') * 10).rstrip('0').rstrip('.')

Just to show a different possibility, I used to_tuple() to achieve the same result.
def my_normalize(dec):
"""
>>> my_normalize(Decimal("12.500"))
Decimal('12.5')
>>> my_normalize(Decimal("-0.12500"))
Decimal('-0.125')
>>> my_normalize(Decimal("0.125"))
Decimal('0.125')
>>> my_normalize(Decimal("0.00125"))
Decimal('0.00125')
>>> my_normalize(Decimal("125.00"))
Decimal('125')
>>> my_normalize(Decimal("12500"))
Decimal('12500')
>>> my_normalize(Decimal("0.000"))
Decimal('0')
"""
if dec is None:
return None
sign, digs, exp = dec.as_tuple()
for i in list(reversed(digs)):
if exp >= 0 or i != 0:
break
exp += 1
digs = digs[:-1]
if not digs and exp < 0:
exp = 0
return Decimal((sign, digs, exp))

Why not use modules 10 from a multiple of 10 to check if there is remainder? No remainder means you can force int()
if (x * 10) % 10 == 0:
x = int(x)
x = 2/1
Output: 2
x = 3/2
Output: 1.5