Simple, configurable Python script to split a single-file dataset into training, testing and validation sets

data_split.py

import random
import math

# Configure paths to your dataset files here
DATASET_FILE = 'data.csv'
FILE_TRAIN = 'train.csv'
FILE_VALID = 'validation.csv'
FILE_TESTS = 'test.csv'

# Set to true if you want to copy first line from main
# file into each split (like CSV header)
IS_CSV = True

# Make sure it adds to 100, no error checking below
PERCENT_TRAIN = 50
PERCENT_VALID = 25
PERCENT_TESTS = 25

data = [l for l in open(DATASET_FILE, 'r')]

train_file = open(FILE_TRAIN, 'w')
valid_file = open(FILE_VALID, 'w')
tests_file = open(FILE_TESTS, 'w')

if IS_CSV:
    train_file.write(data[0])
    valid_file.write(data[0])
    tests_file.write(data[0])
    data = data[1:len(data)]

num_of_data = len(data)
num_train = int((PERCENT_TRAIN/100.0)*num_of_data)
num_valid = int((PERCENT_VALID/100.0)*num_of_data)
num_tests = int((PERCENT_TESTS/100.0)*num_of_data)

data_fractions = [num_train, num_valid, num_tests]
split_data = [[],[],[]]

rand_data_ind = 0

for split_ind, fraction in enumerate(data_fractions):
    for i in range(fraction):
        rand_data_ind = random.randint(0, len(data)-1)
        split_data[split_ind].append(data[rand_data_ind])
        data.pop(rand_data_ind)

for l in split_data[0]:
    train_file.write(l)
    
for l in split_data[1]:
    valid_file.write(l)
    
for l in split_data[2]:
    tests_file.write(l)
    
train_file.close()
valid_file.close()
tests_file.close()

This should work:

line = data.pop(0)
random.shuffle(data)
data.insert(0, line)