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Available datatypes for 'dtype' with NumPy's loadtxt() an genfromtxt

Learn about the available datatypes for 'dtype' with NumPy's loadtxt() an genfromtxt in Python.
Submitted by Pranit Sharma, on February 25, 2023

NumPy is an abbreviated form of Numerical Python. It is used for different types of scientific operations in python. Numpy is a vast library in python which is used for almost every kind of scientific or mathematical operation. It is itself an array which is a collection of various methods and functions for processing the arrays.

Datatypes for 'dtype' with NumPy's loadtxt() an genfromtxt

The numpy.loadtxt loads data from a text file. It takes parameters like fname, dtype, comments, delimiter, and a few more. This function aims to be a fast reader for simply formatted files.

Each row in the input text file must have the same number of values to be able to read all values. If all rows do not have the same number of values, a subset of up to n columns (where n is the least number of values present in all rows) can be read by specifying the columns via usecols.

On the other hand, numpy.genfromtxt loads data from a text file, with missing values handled as specified. Each line past the first skip_header line is split at the delimiter character, and characters following the comments character are discarded.

It takes almost similar parameters like loadtxt. Here, when spaces are used as delimiters, or when no delimiter has been given as input, there should not be any missing data between the two fields.

To check all the available dtypes available in numpy, we can pass the following command in the compiler,

Python code to demonstrate the available datatypes for 'dtype' with NumPy's loadtxt() an genfromtxt

import numpy as np

for i in np.typecodes.items():
    print(i)

Output:

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