At times, we need to make arrays of different types like in AP(equally spaced series of numbers), GP(exponentially spaced series of numbers) or HP(reciprocally spaced series of numbers) to solve various problems, especially while solving some scientific or astronomical problem, in order to reduce the calculations. Python is one of the best languages when it comes to the pre-implemented codes, and is present there almost every time, at the cost of processing speed.

NumPy has a built-in method called arange() which is capable of creating an array of a given integer type(in bytes), with equal spacing between the numbers.

Syntax:arange([start,] stop[, step,][, dtype])

Parameters:

start:This is a default parameter. The value of the first number of the element, the default value of this parameter is 0.stop:This is not a default parameter. This has to be greater than the maximum possible value of the last element. e.g. , If you want the last element to be 8, you should give the stop value as 9 or more, depending upon the difference you want between two consecutive numbers in the array.step:This is also a default parameter. This number will be the difference between the two consecutive elements in the array. The default value of step is 1.dtype:This is also a default parameter. This is the data type of the numbers in NumPy, for simplicity, it is a number(in power of 2) preceded by np.int, e.g., np.int8, np.int16, np.int32.

The function will return an array as per the demand of the user. Let’s see some examples of it:

**Example 1: **To create a simple array starting from 0 to a given number

## Python3

`import` `numpy as np ` ` ` `# Here, the array has only one parameter, ` `# and that is the open ended limit of ` `# last number of the array ` `myArray ` `=` `np.arange(` `8` `) ` `print` `(myArray) ` |

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**Output:**

[0 1 2 3 4 5 6 7]

**Example 2: **To create a simple array starting from a given number to another number

## Python3

`import` `numpy as np ` ` ` ` ` `# This line has two parameters ` `# The first one is the closed end begining limit ` `# The second one is the open end end limit ` `mySecondArray ` `=` `np.arange(` `1` `, ` `6` `) ` `print` `(mySecondArray) ` |

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**Output:**

[1 2 3 4 5]

**Example 3: **To create an array from a given number to another number with a given interval.

## Python3

`import` `numpy as np ` ` ` `# This line has two parameters ` `# The first one is the closed end begining limit ` `# The second one is the open end end limit ` `# The third one is the steps(difference between ` `# two elements in the array) ` `myThirdArray ` `=` `np.arange(` `2` `, ` `12` `, ` `2` `) ` `print` `(myThirdArray) ` |

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**Output:**

[ 2 4 6 8 10]

**Example 4: **We use dtype especially in the cases when we want to deal with images or some other sort of computation.

## Python3

`import` `numpy as np ` ` ` `# This line has two parameters ` `# The first one is the closed end begining limit ` `# The second one is the open end end limit ` `# The third one is the steps(difference between ` `# two elements in the array) ` `myForthArray ` `=` `np.arange(` `5` `, ` `101` `, ` `10` `, np.int32) ` `print` `(myForthArray) ` |

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**Output:**

[ 5 15 25 35 45 55 65 75 85 95]

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