decisiontree.py

from sklearn.tree import DecisionTreeClassifier
import pandas as pd

# create a matrix including the data
data = [[8,8,'dog'],[50,40,'dog'],[8,9,'cat'],[15,12,'dog'],[9,9.8,'cat']]

# generating a dataframe from the matrix 
df = pd.DataFrame(data, columns = ['weight','height','label'])

# defining predictors
X = df[['weight','height']]

# definig the target variable and mapping it to 1 for dog and 0 for cat
y = df['label'].replace({'dog':1, 'cat':0})

# instantiating the model
tree = DecisionTreeClassifier() 

# fitting the model
model = tree.fit(X,y)