numpy.arange() function creates an array of evenly spaced values within a given interval. It is similar to Python's built-in range() function but returns a NumPy array instead of a list.

Let's understand with a simple example:

importnumpyasnp#create an arrayarr=np.arange(5,10)print(arr)

[5 6 7 8 9]

Syntax of numpy.arange():

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

Parameters of numpy():

• start (optional):The starting value of the sequence. Default is 0.
• stop (required):The endpoint of the sequence, exclusive.
• step (optional): The spacing between consecutive values. Default is 1.
• dtype (optional):The desired data type of the output array.

Return Type:

• Array of evenly spaced values.

Specify Start and Stop

Generate a sequence of integers starting from 5 to 14.

importnumpyasnp# Creating a sequence of numbers from 0 to 9sequence=np.arange(10)print("Basic Sequence:",sequence)

Basic Sequence: [0 1 2 3 4 5 6 7 8 9]

Floating-Point Step Size

Generate a sequence of floating-point numbers.

importnumpyasnp# Creating a sequence of floating-point numbers from 0 to 1# with a step size of 0.2 using np.arange()sequence=np.arange(0,1,0.2)print("Floating-Point Sequence:",sequence)

Floating-Point Sequence: [0.  0.2 0.4 0.6 0.8]

Combining with Conditional Filtering

Generate a sequence and filter specific values.

importnumpyasnp# Creating a sequence of numbers from 0 to 20sequence=np.arange(0,20,3)# Filtering the sequence to include only values greater than 10filtered=sequence[sequence>10]print("Filtered Sequence:",filtered)

Filtered Sequence: [12 15 18]

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