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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
I have a csv file without headers which I'm importing into python using pandas. The last column is the target class, while the rest of the columns are pixel values for images. How can I go ahead and split this dataset into a training set and a testing set (3 : 2)?
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Python Code:
import numpy as np
import pandas as pd
dataset = load_data()
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(dataset.iloc[:, :-1], dataset.iloc[:, -1], test_size=0.4,
                                                    random_state=42)
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