numpy.loadtxt — NumPy v1.13 Manual (original) (raw)

fname : file, str, or pathlib.Path

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, optional

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. In this case, the number of columns used must match the number of fields in the data-type.

comments : str or sequence, optional

The characters or list of characters used to indicate the start of a comment; default: ‘#’.

delimiter : str, optional

The string used to separate values. By default, this is any whitespace.

converters : dict, optional

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}. Converters can also be used to provide a default value for missing data (but see also genfromtxt):converters = {3: lambda s: float(s.strip() or 0)}. Default: None.

skiprows : int, optional

Skip the first skiprows lines; default: 0.

usecols : int or sequence, optional

Which columns to read, with 0 being the first. For example, usecols = (1,4,5) will extract the 2nd, 5th and 6th columns. The default, None, results in all columns being read.

New in version 1.11.0.

Also when a single column has to be read it is possible to use an integer instead of a tuple. E.g usecols = 3 reads the fourth column the same way as usecols = (3,)` would.

unpack : bool, optional

If True, the returned array is transposed, so that arguments may be unpacked using x, y, z = loadtxt(...). When used with a structured data-type, arrays are returned for each field. Default is False.

ndmin : int, optional

The returned array will have at least ndmin dimensions. Otherwise mono-dimensional axes will be squeezed. Legal values: 0 (default), 1 or 2.

New in version 1.6.0.