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Genfromtxt introduction

Let's take a look at the definition of genfromtxt:

Numpy.genfromtxt (fname, dtype=, comments='#', delimiter=None, skip_header=0, skip_footer=0, converters=None, missing_values=None, filling_values=None, usecols=None, names=None, excludelist=None, deletechars= "! # $% &'() * +, -. /:; @ [\] ^ {|} ~", replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i', unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None, encoding='bytes')

Genfromtxt can accept multiple parameters, of which only fname is required, and the rest are optional.

Fname can take many forms, such as file, str, pathlib.Path, list of str, or generator.

If it is a separate str, the default is the name of the local or remote file. If it is a list of str, then each str is treated as a line of data in the file. If a remote file is passed in, the file is automatically downloaded to the local directory.

Genfromtxt can also automatically identify whether a file is compressed, and currently supports two compression types: gzip and bz2.

Next, let's take a look at the common applications of genfromtxt:

Before using it, you usually need to import two libraries:

From io import StringIOimport numpy as np

StringIO generates a String object that can be used as input to genfromtxt.

Let's first define a StringIO that contains different types:

S = StringIO (u "1pr 1.3 pr abcde")

This StringIO contains an int, a float, and a str. And the separator is,.

Let's take a look at the simplest use of genfromtxt:

In [65]: data = np.genfromtxt (s) In [66]: dataOut [66]: array (nan)

Because the default delimiter is delimiter=None, the data in StringIO is converted into an array as a whole, resulting in nan.

Let's add a comma separator:

In [67]: _ = s.seek (0) In [68]: data = np.genfromtxt (",") In [69]: dataOut [69]: array ([1,1.3, nan])

There is output this time, but the last string is nan because it cannot be converted to float.

Notice that we need to reset the pointer of StringIO to the beginning of the file on the first line. Here we use s.seek (0).

So how do you convert the last str? We need to specify dtype manually:

In [74]: _ = s.seek (0) In [75]: data = np.genfromtxt (",") In [76]: dataOut [76]: array ([1,1.3, nan])

Above we specify that all array types are float, and we can specify the type for each element of the array separately:

In [77]: _ = s.seek (0) In [78]: data = np.genfromtxt (spark dtype = [int,float,'S5'], delimiter= ",") In [79]: dataOut [79]: array ((1,1.3, baked abcde'), dtype= [('f0boy,')

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