numpy.loadtxt Skipping multiple rows

Question

I believe the title of this thread explains what I am looking for. I am curious to know what the syntax is for skipping multiple rows; I can\'t seem to find such information

Answer 1

Use help(np.loadtxt). You'll find the skiprows parameter will allow you to skip the first N rows:

In [1]: import numpy as np

In [2]: help(np.loadtxt)
Help on function loadtxt in module numpy.lib.npyio:

loadtxt(fname, dtype=<type 'float'>, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0)
    ...
    skiprows : int, optional
        Skip the first `skiprows` lines; default: 0.

Thus, to skip N rows, you'd say

np.loadtxt(fname, skiprows=N)

---

If you need to filter rows other than the first N rows, use np.genfromtxt which can take an iterator which yields strings as its first argument:

with open(filename, 'r') as f:
    lines = (line for line in f if predicate(line))
    arr = np.genfromtxt(lines)

---

To skip a sequence of rows in the middle, such as rows 47--50, you could use itertools like this:

import itertools as IT

with open(filename, 'r') as f:
    lines = IT.chain(IT.islice(f, 46), IT.islice(f, 4, None))
    arr = np.genfromtxt(lines)

Answer 2

If you already know the row numbers you wish to skip, then you can also use:

import numpy as np
InputFile = './Filename.txt'
Dataset = np.loadtxt(InputFile, skiprows= 0 + 1 + 2 + 3 + 4 + 5)
print(Dataset)

This will skip the first five rows and print the remaining data.