numpy.arange() in Python

The arange([start,] stop[, step,][, dtype]) : Returns an array with evenly spaced elements as per the interval. The interval mentioned is half-opened i.e. [Start, Stop)

Parameters :

```start : [optional] start of interval range. By default start = 0
stop  : end of interval range
step  : [optional] step size of interval. By default step size = 1,
For any output out, this is the distance between two adjacent values, out[i+1] - out[i].
dtype : type of output array```

Return:

```Array of evenly spaced values.
Length of array being generated  = Ceil((Stop - Start) / Step) ```

Example:

Python3

 `# Python Programming illustrating``# numpy.arange method` `import` `numpy as geek` `print``(``"A\n"``, geek.arange(``4``).reshape(``2``, ``2``), ``"\n"``)``print``(``"A\n"``, geek.arange(``4``, ``10``), ``"\n"``)``print``(``"A\n"``, geek.arange(``4``, ``20``, ``3``), ``"\n"``)`

Output :

```A
[[0 1]
[2 3]]

A
[4 5 6 7 8 9]

A
[ 4  7 10 13 16 19]```

Note:

• These NumPy-Python programs wonâ€™t run on onlineID, so run them on your systems to explore them.
• The advantage of numpy.arange() over the normal in-built range() function is that it allows us to generate sequences of numbers that are not integers.

Example:

Python3

 `# Python Programming illustrating``# numpy.arange method` `import` `numpy as np` `# Printing all numbers from 1 to ``# 2 in steps of 0.1``print``(np.arange(``1``, ``2``, ``0.1``))`

Output:

`[1.  1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9]`

If you try it with the range() function, you get a TypeError.

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