Skip to content
Related Articles

Related Articles

numpy.loadtxt() in Python
  • Last Updated : 11 Dec, 2018

numpy.load() in Python is used load data from a text file, with aim to be a fast reader for simple text files.

Note that each row in the text file must have the same number of values.

Syntax: numpy.loadtxt(fname, dtype=’float’, comments=’#’, delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0)

Parameters:
fname : File, filename, or generator to read. If the filename extension is .gz or .bz2, the file is first decompressed. Note that generators should return byte strings for Python 3k.
dtype : Data-type of the resulting array; default: float. If this is a structured data-type, the resulting array will be 1-dimensional, and each row will be interpreted as an element of the array.
delimiter : The string used to separate values. By default, this is any whitespace.
converters : A dictionary mapping column number to a function that will convert that column to a float. E.g., if column 0 is a date string: converters = {0: datestr2num}. Default: None.
skiprows : Skip the first skiprows lines; default: 0.

Returns: ndarray



Code #1:




# Python program explaining 
# loadtxt() function
import numpy as geek
  
# StringIO behaves like a file object
from io import StringIO   
  
c = StringIO("0 1 2 \n3 4 5")
d = geek.loadtxt(c)
  
print(d)

Output :

[[ 0.  1.  2.]
 [ 3.  4.  5.]]

 
Code #2:




# Python program explaining 
# loadtxt() function
import numpy as geek
  
# StringIO behaves like a file object
from io import StringIO   
  
c = StringIO("1, 2, 3\n4, 5, 6")
x, y, z = geek.loadtxt(c, delimiter =', ', usecols =(0, 1, 2), 
                                                unpack = True)
  
print("x is: ", x)
print("y is: ", y)
print("z is: ", z)

Output :

x is:  [ 1.  4.]
y is:  [ 2.  5.]
z is:  [ 3.  6.]

 
Code #3:




# Python program explaining 
# loadtxt() function
import numpy as geek
  
# StringIO behaves like a file object
from io import StringIO   
  
d = StringIO("M 21 72\nF 35 58")
e = geek.loadtxt(d, dtype ={'names': ('gender', 'age', 'weight'),
                                  'formats': ('S1', 'i4', 'f4')})
  
print(e)

Output :

[(b'M', 21,  72.) (b'F', 35,  58.)]

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up
Recommended Articles
Page :