# 1. Importing new CSV data in pandas dataframes
import pandas as pd
data = pd.read_csv("iris_extension.csv")

# 2. Separating labels from data
y = data["label"]
data = data.drop(columns=["label"])
x = data.to_numpy()

# 3. Loading a trained model
import pickle
model = pickle.load(open('iris_classif_model.sav', 'rb'))
y_pred = model.predict(x)

# 4. Evaluating the model with the new data
from sklearn.metrics import classification_report, confusion_matrix
print("\n *************** MODEL EVALUATION ****************")
print("Confusion matrix:")
print(confusion_matrix(y, y_pred))
print(classification_report(y,y_pred))