[python] Easy pretty printing of floats in python?

I have a list of floats. If I simply print it, it shows up like this:

[9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]

I could use print "%.2f", which would require a for loop to traverse the list, but then it wouldn't work for more complex data structures. I'd like something like (I'm completely making this up)

>>> import print_options
>>> print_options.set_float_precision(2)
>>> print [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]
[9.0, 0.05, 0.03, 0.01, 0.06, 0.08]

This question is related to python printing formatting floating-point

The answer is


I agree with SilentGhost's comment, the for loop isn't that bad. You can achieve what you want with:

l = [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]
for x in l: print "%0.2f" % (x)

To control the number of significant digits, use the format specifier %g.

Let's name Emile's solution prettylist2f. Here is the modified one:

prettylist2g = lambda l : '[%s]' % ', '.join("%.2g" % x for x in l)

Usage:

>>> c_e_alpha_eps0 = [299792458., 2.718281828, 0.00729735, 8.8541878e-12]
>>> print(prettylist2f(c_e_alpha_eps0)) # [299792458.00, 2.72, 0.01, 0.00]
>>> print(prettylist2g(c_e_alpha_eps0)) # [3e+08, 2.7, 0.0073, 8.9e-12]

If you want flexibility in the number of significant digits, use f-string formatting instead:

prettyflexlist = lambda p, l : '[%s]' % ', '.join(f"{x:.{p}}" for x in l)
print(prettyflexlist(3,c_e_alpha_eps0)) # [3e+08, 2.72, 0.0073, 8.85e-12]

I believe that Python 3.1 will print them nicer by default, without any code changing. But that is useless if you use any extensions that haven't been updated to work with Python 3.1


Note that you can also multiply a string like "%.2f" (example: "%.2f "*10).

>>> print "%.2f "*len(yourlist) % tuple(yourlist)
2.00 33.00 4.42 0.31 

You could use pandas.

Here is an example with a list:

In: import pandas as P
In: P.set_option('display.precision',3)
In: L = [3.4534534, 2.1232131, 6.231212, 6.3423423, 9.342342423]
In: P.Series(data=L)
Out: 
0    3.45
1    2.12
2    6.23
3    6.34
4    9.34
dtype: float64

If you have a dict d, and you want its keys as rows:

In: d
Out: {1: 0.453523, 2: 2.35423234234, 3: 3.423432432, 4: 4.132312312}

In: P.DataFrame(index=d.keys(), data=d.values())
Out:  
    0
1   0.45
2   2.35
3   3.42
4   4.13

And another way of giving dict to a DataFrame:

P.DataFrame.from_dict(d, orient='index')

As noone has added it, it should be noted that going forward from Python 2.6+ the recommended way to do string formating is with format, to get ready for Python 3+.

print ["{0:0.2f}".format(i) for i in a]

The new string formating syntax is not hard to use, and yet is quite powerfull.

I though that may be pprint could have something, but I haven't found anything.


You can do:

a = [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]
print ["%0.2f" % i for i in a]

I just ran into this problem while trying to use pprint to output a list of tuples of floats. Nested comprehensions might be a bad idea, but here's what I did:

tups = [
        (12.0, 9.75, 23.54),
        (12.5, 2.6, 13.85),
        (14.77, 3.56, 23.23),
        (12.0, 5.5, 23.5)
       ]
pprint([['{0:0.02f}'.format(num) for num in tup] for tup in tups])

I used generator expressions at first, but pprint just repred the generator...


The most easy option should be to use a rounding routine:

import numpy as np
x=[9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]

print('standard:')
print(x)
print("\nhuman readable:")
print(np.around(x,decimals=2))

This produces the output:

standard:
[9.0, 0.053, 0.0325754, 0.0108928, 0.0557025, 0.0793303]

human readable:
[ 9.    0.05  0.03  0.01  0.06  0.08]

print "[%s]"%", ".join(map(str,yourlist))

This will avoid the rounding errors in the binary representation when printed, without introducing a fixed precision constraint (like formating with "%.2f"):

[9.0, 0.053, 0.0325754, 0.0108928, 0.0557025, 0.0793303]

First, elements inside a collection print their repr. you should learn about __repr__ and __str__.

This is the difference between print repr(1.1) and print 1.1. Let's join all those strings instead of the representations:

numbers = [9.0, 0.053, 0.0325754, 0.0108928, 0.0557025, 0.07933]
print "repr:", " ".join(repr(n) for n in numbers)
print "str:", " ".join(str(n) for n in numbers)

List comps are your friend.

print ", ".join("%.2f" % f for f in list_o_numbers)

Try it:

>>> nums = [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999]
>>> print ", ".join("%.2f" % f for f in nums)
9.00, 0.05, 0.03, 0.01

I had this problem, but none of the solutions here did exactly what I wanted (I want the printed output to be a valid python expression), so how about this:

prettylist = lambda l : '[%s]' % ', '.join("%.2f" % f for f in l)

Usage:

>>> ugly = [9.0, 0.052999999999999999, 0.032575399999999997,
            0.010892799999999999, 0.055702500000000002, 0.079330300000000006]
>>> prettylist = lambda l : '[%s]' % ', '.join("%.2f" % f for f in l)
>>> print prettylist(ugly)
[9.00, 0.05, 0.03, 0.01, 0.06, 0.08]

(I know .format() is supposed to be the more standard solution, but I find this more readable)


The code below works nice to me.

list = map (lambda x: float('%0.2f' % x), list)

l = [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]

Python 2:

print ', '.join('{:0.2f}'.format(i) for i in l)

Python 3:

print(', '.join('{:0.2f}'.format(i) for i in l))

Output:

9.00, 0.05, 0.03, 0.01, 0.06, 0.08

A more permanent solution is to subclass float:

>>> class prettyfloat(float):
    def __repr__(self):
        return "%0.2f" % self

>>> x
[1.290192, 3.0002, 22.119199999999999, 3.4110999999999998]
>>> x = map(prettyfloat, x)
>>> x
[1.29, 3.00, 22.12, 3.41]
>>> y = x[2]
>>> y
22.12

The problem with subclassing float is that it breaks code that's explicitly looking for a variable's type. But so far as I can tell, that's the only problem with it. And a simple x = map(float, x) undoes the conversion to prettyfloat.

Tragically, you can't just monkey-patch float.__repr__, because float's immutable.

If you don't want to subclass float, but don't mind defining a function, map(f, x) is a lot more concise than [f(n) for n in x]


As of Python 3.6, you can use f-strings:

list_ = [9.0, 0.052999999999999999, 
         0.032575399999999997, 0.010892799999999999, 
         0.055702500000000002, 0.079330300000000006]

print(*[f"{element:.2f}" for element in list_])
#9.00 0.05 0.03 0.01 0.06 0.08

You can use print parameters while keeping code very readable:

print(*[f"{element:.2f}" for element in list_], sep='|', end='<--')
#9.00|0.05|0.03|0.01|0.06|0.08<--

a = [9.0, 0.052999999999999999, 0.032575399999999997, 0.010892799999999999, 0.055702500000000002, 0.079330300000000006]
print(", ".join(f'{x:.2f}' for x in a))

f'{x}' means f-string equal to str(x); f'{x:.2f}' means x will be present as float number with two decimal places.


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