**NumPy frombuffer() Function:**

**np.frombuffer: **The frombuffer() function of the NumPy module is used to interpret a buffer as a 1-dimensional array.

Using the given buffer, this function creates an array.

**Syntax:**

numpy.frombuffer(buffer, dtype=float, count=-1, offset=0)

**Parameters**

**buffer:** This is Required. It is an object that exposes the buffer interface.

**dtype:** This is optional. It denotes the data type of the array returned. float is the default value.

**count:** This is optional. It denotes the number of items to read. The default value is -1, which means all the data present.

**offset:** This is optional. Begin reading from this offset in the buffer (in bytes). The default value is 0.

**Return Value:**

The buffer’s array version is returned.

## NumPy frombuffer() Function in Python

**Example**

**Approach:**

- Import numpy module using the import keyword
- Give some random string and keep prefix as ‘b’ to it
- Store it in a variable.
- Pass the given array and datatype as S1 as arguments to the frombuffer() function

of the numpy module and store it in another variable. - Here it creates a 1-Dimensional NumPy array from the above buffer
- Print the 1-Dimensional numpy array from the above buffer.
- Pass the given array, datatype as S1 and some random count as arguments to the

frombuffer() function of the numpy module and store it in another variable. - Print the above-obtained array.
- Pass the given array, datatype as S1, some random count and offset values as arguments to the

frombuffer() function of the numpy module and store it in another variable. - Print the above-obtained array(with count and offset).
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Give some random string and keep prefix as 'b' to it # Store it in a variable. gvn_buffr = b"Btechgeeks" # Pass the given array and datatype as S1 as arguments to the frombuffer() function # of the numpy module and store it in another variable. # Here it creates 1-Dimensional numpy array from the above buffer rslt_arry1 = np.frombuffer(gvn_buffr, dtype='S1') # Print the 1-Dimensional numpy array from the above buffer. print("The 1-Dimensional numpy array from the above buffer:\n", rslt_arry1) # Pass the given array, datatype as S1 and some random count as arguments to the # frombuffer() function of the numpy module and store it in another variable. rslt_arry2 = np.frombuffer(gvn_buffr, dtype='S1', count=4) # Print the above obtained array. print("The above obtained Array:\n", rslt_arry2) # Pass the given array, datatype as S1, some random count and offset values as arguments to the # frombuffer() function of the numpy module and store it in another variable. rslt_arry3 = np.frombuffer(gvn_buffr, dtype='S1', count=4, offset=5) # Print the above obtained array(with count and offset). print("The above obtained array(with count and offset).:\n", rslt_arry3)

**Output:**

The 1-Dimensional numpy array from the above buffer: [b'B' b't' b'e' b'c' b'h' b'g' b'e' b'e' b'k' b's'] The above obtained Array: [b'B' b't' b'e' b'c'] The above obtained array(with count and offset).: [b'g' b'e' b'e' b'k']