What is the numpy.concatenate() function in Python?

Overview

The concatenate() function in Python is used to concatenate or join a sequence of input arrays along an existing axis.

Syntax

numpy.concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind")
Syntax for the numpy.concatenate() function

Parameter value

The concatenate() function takes the following parameter values.

  • (a1, a2, ...): These are the input arrays to be concatenated. This is a required parameter.
  • axis: This is the given axis along which the input arrays will be joined. This is an optional parameter.
  • out: This is the destination path for the result. This is an optional parameter.
  • dtype: This is the data type of the desired output array. The value can be inferred from the data type of the input arrays. This is an optional parameter.
  • casting: This controls the kind of datacasting that may occur. This is an optional parameter.

Return value

The concatenate() function returns the concatenated array.

Example

import numpy as np
# creating input arrays
a = np.array([[1, 2, 3], [4, 5, 6]])
b = np.array([[7, 8, 9]])
# concatenating the arrays
myarray = np.concatenate((a,b), axis=0)
# printing the concatenated array
print(myarray)

Explanation

  • Line 1: We import the numpy module.
  • Lines 3–4: We create input arrays, a and b, using the np.array() function.
  • Line 7: We concatenate the input arrays using the np.concatenate() function. The result is assigned to a variable, myarray.
  • Line 10: We print the concatenated array, myarray.

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