numpy.arange

numpy.arange([start, ]stop, [step, ]dtype=None)

Return evenly spaced values within a given interval.
Values are generated within the halfopen interval [start, stop)
(in other words, the interval including start
but excluding stop
). For integer arguments the function is equivalent to the Python builtin range
function, but returns an ndarray rather than a list.
When using a noninteger step, such as 0.1, the results will often not be consistent. It is better to use numpy.linspace
for these cases.
Parameters: 

start : number, optional 
Start of interval. The interval includes this value. The default start value is 0. 
stop : number 
End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point roundoff affects the length of out . 
step : number, optional 
Spacing between values. For any output out , this is the distance between two adjacent values, out[i+1]  out[i] . The default step size is 1. If step is specified as a position argument, start must also be given. 
dtype : dtype 
The type of the output array. If dtype is not given, infer the data type from the other input arguments. 
Returns: 

arange : ndarray 
Array of evenly spaced values. For floating point arguments, the length of the result is ceil((stop  start)/step) . Because of floating point overflow, this rule may result in the last element of out being greater than stop . 
See also

linspace
 Evenly spaced numbers with careful handling of endpoints.

ogrid
 Arrays of evenly spaced numbers in Ndimensions.

mgrid
 Gridshaped arrays of evenly spaced numbers in Ndimensions.
Examples
>>> np.arange(3)
array([0, 1, 2])
>>> np.arange(3.0)
array([ 0., 1., 2.])
>>> np.arange(3,7)
array([3, 4, 5, 6])
>>> np.arange(3,7,2)
array([3, 5])