# Return a description for the given data type code in Python

To return a description for the given data type code, use the typename() method in Python Numpy. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.

## Steps

At first, import the required library −

import numpy as np

Our array −

arr = ['S1', '?', 'B', 'D', 'G', 'F', 'I', 'H', 'L', 'O', 'Q', 'S', 'U', 'V', 'b', 'd', 'g', 'f', 'i', 'h', 'l', 'q']

To return a description for the given data type code, use the typename() method in Python Numpy. The 1st argument is the Data type code −

for i in arr:
print(i, ' : ', np.typename(i))

## Example

import numpy as np

# declaring
arr = ['S1', '?', 'B', 'D', 'G', 'F', 'I', 'H', 'L', 'O', 'Q', 'S', 'U', 'V', 'b', 'd', 'g', 'f', 'i', 'h', 'l', 'q']

# To return a description for the given data type code, use the typename() method in Python Numpy
# The 1st argument is the Data type code
for i in arr:
print(i, ' : ', np.typename(i))

## Output

S1 : character
? : bool
B : unsigned char
D : complex double precision
G : complex long double precision
F : complex single precision
I : unsigned integer
H : unsigned short
L : unsigned long integer
O : object
Q : unsigned long long integer
S : string
U : unicode
V : void
b : signed char
d : double precision
g : long precision
f : single precision
i : integer
h : short
l : long integer
q : long long integer