### arange
~~~python arange(start, stop, step,, dtype=None) ~~~
Return evenly spaced values within a given interval.
Values are generated within the half-open interval ``start, stop)`` (in other words, the interval including `start` but excluding `stop`). For integer arguments the function is equivalent to the Python built-in `range` function, but returns an ndarray rather than a list. When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use `numpy.linspace` for these cases. #### Parameters ???+ info "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 round-off affects the length of `out`. ???+ info "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. ???+ info "dtype : dtype" The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. #### Returns ???+ info "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 numpy.linspace : Evenly spaced numbers with careful handling of endpoints. numpy.ogrid: Arrays of evenly spaced numbers in N-dimensions. numpy.mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions. #### Examples ~~~python >>> 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]) ~~~