import pandas as pd
from sklearn.model_selection import train_test_split

def get_data():
	'''
	Simple function, that ready in the data, cleans it
	and returns it already split and train and test
	'''
	complete_data = pd.read_csv('../datasets/complete-set.csv')
	complete_data.dropna()
	texts = complete_data['content'].to_numpy()

	labels = complete_data['labels'].to_numpy()

	print('Data will be returned as: ')
	print('x_train, x_test, y_train, y_test')
	return train_test_split(texts,labels)

51e4a460b06fdc717cb5aba2e0e8d078e6bf9605
<mask token>

<mask token>


def get_data():
    """
	Simple function, that ready in the data, cleans it
	and returns it already split and train and test
	"""
    complete_data = pd.read_csv('../datasets/complete-set.csv')
    complete_data.dropna()
    texts = complete_data['content'].to_numpy()
    labels = complete_data['labels'].to_numpy()
    print('Data will be returned as: ')
    print('x_train, x_test, y_train, y_test')
    return train_test_split(texts, labels)

import pandas as pd
from sklearn.model_selection import train_test_split


def get_data():
    """
	Simple function, that ready in the data, cleans it
	and returns it already split and train and test
	"""
    complete_data = pd.read_csv('../datasets/complete-set.csv')
    complete_data.dropna()
    texts = complete_data['content'].to_numpy()
    labels = complete_data['labels'].to_numpy()
    print('Data will be returned as: ')
    print('x_train, x_test, y_train, y_test')
    return train_test_split(texts, labels)

import pandas as pd
from sklearn.model_selection import train_test_split

def get_data():
	'''
	Simple function, that ready in the data, cleans it
	and returns it already split and train and test
	'''
	complete_data = pd.read_csv('../datasets/complete-set.csv')
	complete_data.dropna()
	texts = complete_data['content'].to_numpy()

	labels = complete_data['labels'].to_numpy()

	print('Data will be returned as: ')
	print('x_train, x_test, y_train, y_test')
	return train_test_split(texts,labels)
