Python中的 numpy.loadtxt()

Python中的numpy.load()用于从文本文件中加载数据，旨在成为简单文本文件的快速阅读器。

请注意，文本文件中的每一行必须具有相同数量的值。

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

代码#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)

输出 ：

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

代码#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)

输出 ：

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

代码#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)

输出 ：

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