Say I have a .txt file with many rows and columns of data and a list containing integer values. How would I load the row numbers in the text file which match the integers in the list?

To illustrate, say I have a list of integers:

a = [1,3,5]

How would I read only rows 1,3 and 5 from a text file into an array?

The loadtxt routine in numpy let's you both skip rows and use particular columns. But I can't seem to find a way to do something along the lines of (ignoring incorrect syntax):

new_array = np.loadtxt('data.txt', userows=a, unpack='true')

Thank you.

Given this file:

1,2,3
4,5,6
7,8,9
10,11,12
13,14,15
16,17,18
19,20,21

You can use the csv module to get the desired np array:

import csv
import numpy as npdesired=[1,3,5]
with open('/tmp/test.csv', 'r') as fin:reader=csv.reader(fin)result=[[int(s) for s in row] for i,row in enumerate(reader) if i in desired]print(np.array(result))   

Prints:

[[ 4  5  6][10 11 12][16 17 18]]