import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer

data = {
    'label': [0, 1, 0, 1],
    'text': ['first bit of text', 'second bit of text', 'third text', 'text number four']
}
data = pd.DataFrame.from_dict(data)

# Form vocab dictionary
vectorizer = CountVectorizer()
vectorizer.fit_transform(data['text'].tolist())
vocab_text = vectorizer.vocabulary_

# Convert text
def convert_text(text):
    text_list = text.split(' ')
    return [vocab_text[t]+1 for t in text_list]

data['text'] = data['text'].apply(convert_text)

# Get X and y matrices
y = np.array(data['label'])
X = np.array(data['text'])`