588

How do I create a list of numbers between two values? For example, a list between 11 and 16:

[11, 12, 13, 14, 15, 16]

13 Answers 13

1035

Use range. In Python 2, it returns a list directly:

>>> range(11, 17)
[11, 12, 13, 14, 15, 16]

In Python 3, range is an iterator. To convert it to a list:

>>> list(range(11, 17))
[11, 12, 13, 14, 15, 16]

Note: The second number in range(start, stop) is exclusive. So, stop = 16+1 = 17.


To increment by steps of 0.5, consider using numpy's arange() and .tolist():

>>> import numpy as np
>>> np.arange(11, 17, 0.5).tolist()

[11.0, 11.5, 12.0, 12.5, 13.0, 13.5,
 14.0, 14.5, 15.0, 15.5, 16.0, 16.5]

See: How do I use a decimal step value for range()?

9
  • 2
    Awesome! Exactly what I was looking for! Is there also a way to increment by smaller values like 0.5 than just 1? so [11.0, 11.5, 12.0 ...... 16.0]
    – lorde
    Commented Aug 16, 2013 at 4:50
  • 4
    @lorde You can increment by more than 1 with a third step parameter but that's still an int -- not float. You can't do that exactly in the standard lib.
    – Jared
    Commented Aug 16, 2013 at 4:53
  • @Jared can I make a list by dropping some value after some interval. like [1,2,3,5,6,7,9,10,11,13,14,15,17,18,19]
    – user6390698
    Commented Jun 7, 2016 at 9:12
  • 2
    Good for telling about Python 2.x and 3.x.
    – Sigur
    Commented Apr 15, 2017 at 16:24
  • 1
    If you're working in circumstances where numpy is unwanted, consider (where x=11, y=17, and step=0.5 as above): a_range = [x]+[x+(step*i) for i in range(int((y-x)/step))] Commented Oct 3, 2018 at 17:53
45

You seem to be looking for range():

>>> x1=11
>>> x2=16
>>> range(x1, x2+1)
[11, 12, 13, 14, 15, 16]
>>> list1 = range(x1, x2+1)
>>> list1
[11, 12, 13, 14, 15, 16]

For incrementing by 0.5 instead of 1, say:

>>> list2 = [x*0.5 for x in range(2*x1, 2*x2+1)]
>>> list2
[11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0]
2
  • x*increment, but what do you mean by 2*startvalue, what for? would you explain please? Commented Mar 27, 2017 at 7:30
  • This does not work in Python 3+; instead, there you need list(range(x1, x2+1)).
    – Convexity
    Commented Apr 16, 2024 at 12:49
16

Try:

range(x1, x2+1)  

That is a list in Python 2.x and behaves mostly like a list in Python 3.x. If you are running Python 3 and need a list that you can modify, then use:

list(range(x1, x2+1))
9

Use list comprehension in python. Since you want 16 in the list too.. Use x2+1. Range function excludes the higher limit in the function.

list=[x for x in range(x1, x2+1)]
4
  • 4
    If you use range() no need to use a list comprehension Commented Apr 17, 2018 at 10:59
  • @BillalBegueradj In Python3, range() returns a generator-like object instead of a list. It's basically the same as xrange() in Python 2. You're right that list comprehension isn't needed. The list() builtin function is easier: list(range(x1, x2+1)). Commented Jan 19, 2020 at 5:14
  • @MikeHousky no, range is absolutely not a generator-like object. It is a sequence type object. Unless you want to do things like append to the sequence, you can probably just use the range object directly. Commented Oct 19, 2021 at 15:37
  • 1
    Using a list-comprehension here is pointless. [x for x in whatever] should always just be list(whatever) Commented Oct 19, 2021 at 15:37
8

If you are looking for range like function which works for float type, then here is a very good article.

def frange(start, stop, step=1.0):
    ''' "range()" like function which accept float type''' 
    i = start
    while i < stop:
        yield i
        i += step
# Generate one element at a time.
# Preferred when you don't need all generated elements at the same time. 
# This will save memory.
for i in frange(1.0, 2.0, 0.5):
    print i   # Use generated element.
# Generate all elements at once.
# Preferred when generated list ought to be small.
print list(frange(1.0, 10.0, 0.5))    

Output:

1.0
1.5
[1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5]
1
  • Why not the one-liner instead? start = 2; step =1; end = 10; z= np.array(range(start*step,step*end))/step; print(z)
    – Mohd
    Commented Nov 11, 2020 at 10:02
7

assuming you want to have a range between x to y

range(x,y+1)

>>> range(11,17)
[11, 12, 13, 14, 15, 16]
>>>

use list for 3.x support

6

I got here because I wanted to create a range between -10 and 10 in increments of 0.1 using list comprehension. Instead of doing an overly complicated function like most of the answers above I just did this

simple_range = [ x*0.1 for x in range(-100, 100) ]

By changing the range count to 100 I now get my range of -10 through 10 by using the standard range function. So if you need it by 0.2 then just do range(-200, 200) and so on etc

5

In python you can do this very eaisly

start=0
end=10
arr=list(range(start,end+1))
output: arr=[0,1,2,3,4,5,6,7,8,9,10]

or you can create a recursive function that returns an array upto a given number:

ar=[]
def diff(start,end):
    if start==end:
        d.append(end)
        return ar
    else:
        ar.append(end)
        return diff(start-1,end) 

output: ar=[10,9,8,7,6,5,4,3,2,1,0]

4

While @Jared's answer for incrementing works for 0.5 step size, it fails for other step sizes due to rounding issues:

np.arange(11, 17, 0.1).tolist()
# [11.0,11.1,11.2,11.299999999999999, ...   16.79999999999998, 16.899999999999977]

Instead I needed something like this myself, working not just for 0.5:

# Example 11->16 step 0.5
s = 11
e = 16
step = 0.5
my_list = [round(num, 2) for num in np.linspace(s,e,(e-s)*int(1/step)+1).tolist()]
# [11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0]

# Example 0->1 step 0.1
s = 0
e = 1
step = 0.1
my_list = [round(num, 2) for num in np.linspace(s,e,(e-s)*int(1/step)+1).tolist()]
# [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
3

The most elegant way to do this is by using the range function however if you want to re-create this logic you can do something like this :

def custom_range(*args):
    s = slice(*args)
    start, stop, step = s.start, s.stop, s.step
    if 0 == step:
        raise ValueError("range() arg 3 must not be zero")
    i = start
    while i < stop if step > 0 else i > stop:
        yield i
        i += step

>>> [x for x in custom_range(10, 3, -1)]

This produces the output:

[10, 9, 8, 7, 6, 5, 4]

As expressed before by @Jared, the best way is to use the range or numpy.arrange however I find the code interesting to be shared.

2
  • list(custom_range(10,3,1)) returns empty list. Commented Jan 11, 2018 at 11:33
  • indeed, like [x for x in range(10, 3, 1)] - the first argument is the start, the second the end and the last the step. ==> stop > start
    – Michael
    Commented Jan 11, 2018 at 11:37
3

Every answer above assumes range is of positive numbers only. Here is the solution to return list of consecutive numbers where arguments can be any (positive or negative), with the possibility to set optional step value (default = 1).

def any_number_range(a,b,s=1):
""" Generate consecutive values list between two numbers with optional step (default=1)."""
if (a == b):
    return a
else:
    mx = max(a,b)
    mn = min(a,b)
    result = []
    # inclusive upper limit. If not needed, delete '+1' in the line below
    while(mn < mx + 1):
        # if step is positive we go from min to max
        if s > 0:
            result.append(mn)
            mn += s
        # if step is negative we go from max to min
        if s < 0:
            result.append(mx)
            mx += s
    return result

For instance, standard command list(range(1,-3)) returns empty list [], while this function will return [-3,-2,-1,0,1]

Updated: now step may be negative. Thanks @Michael for his comment.

5
  • 1
    This assumes your step is positive.
    – Michael
    Commented Jan 10, 2018 at 13:55
  • @Michael, good point. I've updated the code, so now you can have negative steps :) Commented Jan 11, 2018 at 11:11
  • @tgikal, that's right. But what if you don't know what values will be assigned to the arguments of your function and you need sorted return? Commented Sep 6, 2018 at 6:15
  • I don't see any additional features your custom function does that cannot be accomplished using the builtin range function, I guess an example of the improvement would be great, since your current example is basically i_min = -3, i_max = 1 any_number_range(i_max, i_min)) returns [-3,-2,-1,0,1] But, builtin list(range(i_min, i_max + 1)) will return the same values.
    – tgikal
    Commented Sep 6, 2018 at 20:43
  • Try using a negative step when the sequence is decreasing list(range(1,-3, -1)) Commented Jul 17, 2019 at 8:04
0

@YTZ's answer worked great in my case. I had to generate a list from 0 to 10000 with a step of 0.01 and simply adding 0.01 at each iteration did not work due to rounding issues.

Therefore, I used @YTZ's advice and wrote the following function:

import numpy as np


def generate_floating_numbers_in_range(start: int, end: int, step: float):
    """
    Generate a list of floating numbers within a specified range.

    :param start: range start
    :param end: range end
    :param step: range step
    :return:
    """
    numbers = np.linspace(start, end,(end-start)*int(1/step)+1).tolist()
    return [round(num, 2) for num in numbers]
-1

If you're open to numpy, there are a few functions in it that can generate numbers between 11 and 16:

  1. numbers between 11 and 16 with step=0.5: np.arange(11, 16.1, 0.5)
  2. n evenly-spaced numbers between 11 and 16: np.linspace(11, 16, n)
  3. n random integers between 11 and 16: np.random.randint(11, 17, n)
  4. n random numbers between 11 and 16: np.random.rand(n)*(16-11) + 11
  5. n numbers between 11 and 16 that are the log of evenly-spaced numbers (results in a concave curve): np.log(np.linspace(np.e**11, np.e**16, n))
  6. n numbers between 11 and 16 that are the normalization of evenly-spaced numbers on log scale (results in a convex curve): (np.logspace(11, 16, n, base=np.e) - np.e**11)/(np.e**16 - np.e**11)*(16-11) + 11

The numbers generated by rules (1), (2), (5), (6) are plotted as follows (for n=50). As you can see, similar to the built-in range(), the output size of np.arange() is controlled by its step; however, the output size of np.linspace(), np.logspace() and np.random functions are directly controlled by the third positional argument.

plot

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