**NumPy squeeze() Function:**

**Numpy squeeze: **The squeeze() function in NumPy module remove axes of length one from an array

It removes single-dimensional items from the shape of an array.

**Syntax:**

numpy.squeeze(a, axis=None)

**Parameters**

**a:** This is required. It is the input array.

**axis:** This is optional. None, int, or a tuple of ints can be used. Selects a subset of the entries of length one in the shape. An error is raised if an axis is specified with a shape entry greater than one.

**Return Value: **

**NP squeeze: **The input array with all or a subset of the dimensions of length 1 removed is returned.

## NumPy squeeze() Function in Python

**Example1**

**Approach:**

- Import numpy module using the import keyword.
- Pass some random list(multi-dimensional) as an argument to the array() function to create an array.
- Store it in a variable.
- Print the above-given array.
- Print the shape(dimensions) of the given array using the shape function.
- Pass the given array as an argument to the squeeze() function of numpy module to remove the axes of length one from the above given array.
- Store it in another variable.
- Print the above-squeezed array(here axis=None).
- Print the shape of the squeezed array using the shape function.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Pass some random list(multi-dimensional) as an argument to the array() function to # create an array. # Store it in a variable. gvn_arry = np.array([[[4, 12, 1], [6, 9, 2], [7, 5, 3]]]) # Print the above given array. print("The above given array is:") print(gvn_arry) # Print the shape(dimensions) of the given array using the shape function print("Given array shape is:", gvn_arry.shape) # Pass the given array as an argument to the squeeze() function of numpy module # to remove the axes of length one from the above given array # Store it in another variable. rslt_arry = np.squeeze(gvn_arry) # Print the above squeezed array(here axis=None). print("The above squeezed array is:") print(rslt_arry) # Print the shape of the squeezed array using the shape function print("Squeezed array shape is:", rslt_arry.shape)

**Output:**

The above given array is: [[[ 4 12 1] [ 6 9 2] [ 7 5 3]]] Given array shape is: (1, 3, 3) The above squeezed array is: [[ 4 12 1] [ 6 9 2] [ 7 5 3]] Squeezed array shape is: (3, 3)

**Example2**

**Numpy squeeze: **On an axis with a shape greater than one, an array cannot be squeezed.

**Approach:**

- Import numpy module using the import keyword.
- Pass some random list (here with shape (1,3,1)) as an argument to the array() function to create an array.
- Store it in a variable.
- Print the above-given array.
- Print the shape of the given array using the shape function.
- Squeezing an array at an axis with a shape greater than one is impossible. For example, Array has shape = 3 at axis=1, therefore squeezing it at axis=1 will result in an exception.
- Pass the given array, axis = 0 as the arguments to the squeeze() function of numpy module to squeeze the given array at axis=0.
- Store it in another variable.
- Pass the given array, axis = 2 as the arguments to the squeeze() function of numpy module to squeeze the given array at axis=2.
- Store it in another variable.
- Print the above obtained squeezed array at axis = 0
- Print the shape of the squeezed array at axis = 0 using the shape function.
- Print the above obtained squeezed array at axis = 2
- Print the shape of the squeezed array at axis = 2 using the shape function.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Pass some random list(here with shape (1,3,1)) as an argument to the array() function to # create an array. # Store it in a variable. gvn_arry = np.array([[[5],[6],[7]]]) # Print the above given array. print("The above given array is:") print(gvn_arry) # Print the shape(dimensions) of the given array using the shape function print("Given array shape is:", gvn_arry.shape) print() # Squeezing an array at an axis with a shape greater than one is impossible. # For example, Array has shape = 3 at axis=1, therefore squeezing it at # axis=1 will result in an exception. # Pass the given array, axis = 0 as the arguments to the squeeze() function of numpy module # to squeeze the given array at axis=0 # Store it in another variable. rslt_arry1 = np.squeeze(gvn_arry, axis=0) # Pass the given array, axis = 2 as the arguments to the squeeze() function of numpy module # to squeeze the given array at axis=2 # Store it in another variable. rslt_arry2 = np.squeeze(gvn_arry, axis=2) # Print the above obtained squeezed array at axis = 0 print("The above obtained squeezed array at axis = 0:") print(rslt_arry1) # Print the shape of the squeezed array at axis = 0 using the shape function print("The shape of the squeezed array at axis = 0 is:", rslt_arry1.shape) print() # Print the above obtained squeezed array at axis = 2 print("The above obtained squeezed array at axis = 2:") print(rslt_arry2) # Print the shape of the squeezed array at axis = 2 using the shape function print("The shape of the squeezed array at axis = 2 is:", rslt_arry2.shape)

**Output:**

The above given array is: [[[5] [6] [7]]] Given array shape is: (1, 3, 1) The above obtained squeezed array at axis = 0: [[5] [6] [7]] The shape of the squeezed array at axis = 0 is: (3, 1) The above obtained squeezed array at axis = 2: [[5 6 7]] The shape of the squeezed array at axis = 2 is: (1, 3)