Say I have a CSV file.csv in this format:
dfaefew,432,1
vzcxvvz,300,1
ewrwefd,432,0
How to import the second column as a NumPy array and the third column as another one like this:
second = np.array([432, 300, 432])
third = np.array([1, 1, 0])
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2 Answers
numpy.genfromtxt() is the best thing to use here
import numpy as np
csv = np.genfromtxt ('file.csv', delimiter=",")
second = csv[:,1]
third = csv[:,2]
>>> second
Out[1]: array([ 432., 300., 432.])
>>> third
Out[2]: array([ 1., 1., 0.])
1 Comment
Nikhil Gupta
genfromtxt works better than loadtxt in my use case and I had to add dtype=None since my data had a mix of data types that I was reading. Just FYI....
You can use numpy.loadtxt:
In [15]: !cat data.csv
dfaefew,432,1
vzcxvvz,300,1
ewrwefd,432,0
In [16]: second, third = loadtxt('data.csv', delimiter=',', usecols=(1,2), unpack=True, dtype=int)
In [17]: second
Out[17]: array([432, 300, 432])
In [18]: third
Out[18]: array([1, 1, 0])
In [19]: second, third = genfromtxt('data.csv', delimiter=',', usecols=(1,2), unpack=True, dtype=None)
The only change in the arguments is that I used dtype=None, which tells genfromtxt to infer the data type from the values that it finds in the file.
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