How to import csv data file into scikit-learn?

Question

From my understanding, the scikit-learn accepts data in (n-sample, n-feature) format which is a 2D array. Assuming I have data in the form ...

Stock prices    in         


        

Answer 1

This is not a CSV file; this is just a space separated file. Assuming there are no missing values, you can easily load this into a Numpy array called data with

import numpy as np

f = open("filename.txt")
f.readline()  # skip the header
data = np.loadtxt(f)

If the stock price is what you want to predict (your y value, in scikit-learn terms), then you should split data using

X = data[:, 1:]  # select columns 1 through end
y = data[:, 0]   # select column 0, the stock price

Alternatively, you might be able to massage the standard Python csv module into handling this type of file.