Python numpy.loadtxt() The loadtxt() function of Python numpy class loads the data from a text fileand provides a fast reader for simple text files. Syntax
numpy.loadtxt(fname, dtype=<class'float'>, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0, encoding='bytes', max_rows=None)
Parameter fname : This parameter represents a file, filename, or generator to read. If the extension is .gz or .bz2, the file decompressed. dtype : It is an optional parameter. It depicts the data type of returned array, and by default, it is a float.If it is a structured data-type, the array will be of one-dimensional, whereeach row represents as an element of the array. delimiter : This parameter represents a string to separatethe values. By default, it can be any whitespace. converters : It signifies a dictionary used for mapping column number to a function that will convert that column to a float. skiprows : This parameter is used for skipping the first skip rows lines.It is an optional field, and its default value is 0. usecols : This parameter states which columns to read, with 0 being the first. It is also an optional field. unpack : It is an optional parameter and represents Boolean value, and by default, it is false.If passed true, the returned array is transposed, so that the parameters may be unpacked using x, y, z = loadtxt(...). When used with a structured data-type, the arrays are returned for each field. ndmin : It returns an array will have at least ndmin dimensions. encoding : It is used forEncoding and later decoding the inputfile. max_rows : It reads the max_rows lines of content after skiprows lines. Return This function reads the data from the text file. Example 1
# Python program to explain
# numpy.loadtxt() function
importnumpy as np
# StringIO behaves like a file object
fromio import StringIO
n = StringIO("1 2 \n 4 5 9")
m = np.loadtxt(n)
print(m)Output
[[ 1. 2.]
[ 4. 5.]]
Example 2
# Python program to explain
# numpy.loadtxt() function
importnumpy as np
# StringIO behaves like a file object
fromio import StringIO
obj = StringIO("1, 2, 3\n4, 5, 6")
n, m, p = np.loadtxt(obj, delimiter =', ', usecols =(0, 1, 2), unpack = True)
print("value of n: ", n)
print("value of m: ", m)
print("value of p: ", p)Output
value of n: [ 1. 4.]
value of m: [ 2. 5.]
value of p: [ 3. 6.]
