Note that each line 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. Eg, if column 0 is a date string: converters = {0: datestr2num}. Default: None.
skiprows: Skip the first skiprows lines; default: 0.Returns: ndarray
Code # 1:
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Output:
[[0. 1. 2.] [3. 4. 5.]]
Code # 2:
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Output:
x is: [1. 4.] y is: [2. 5.] z is: [3. 6.]
Code # 3:
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Output:
[(b'M', 21, 72.) (b'F', 35, 58.)]
