!python --version

Python 3.10.5

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import LabelEncoder
from deepchecks.tabular import Dataset
from deepchecks.tabular.suites import full_suite

# Load the Titanic dataset
url = "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv"
titanic = pd.read_csv(url)

# Preprocess the data
# Drop irrelevant columns
titanic = titanic.drop(columns=['PassengerId', 'Name', 'Ticket', 'Cabin'])

# Fill missing values
titanic['Age'] = titanic['Age'].fillna(titanic['Age'].median())
titanic['Embarked'] = titanic['Embarked'].fillna('S')

# Encode categorical variables
label_encoder = LabelEncoder()
titanic['Sex'] = label_encoder.fit_transform(titanic['Sex'])
titanic['Embarked'] = label_encoder.fit_transform(titanic['Embarked'])

# Split the data
X = titanic.drop(columns=['Survived'])
y = titanic['Survived']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)

# Train a Random Forest model
model = RandomForestClassifier(random_state=42)
model.fit(X_train, y_train)

# Wrap datasets into Deepchecks Dataset objects
columns = X.columns.tolist()
train_df = pd.DataFrame(X_train, columns=columns)
train_df['Survived'] = y_train

test_df = pd.DataFrame(X_test, columns=columns)
test_df['Survived'] = y_test

dc_train = Dataset(train_df, label='Survived', cat_features=['Sex', 'Embarked'])
dc_test = Dataset(test_df, label='Survived', cat_features=['Sex', 'Embarked'])

# Run the full Deepchecks suite
suite = full_suite()
suite_result = suite.run(train_dataset=dc_train, test_dataset=dc_test, model=model)

/home/rajaraman/miniconda3/envs/ml3105/lib/python3.10/site-packages/deepchecks/utils/abstracts/weak_segment_abstract.py:57: FutureWarning:

Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value 'Other' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.

/home/rajaraman/miniconda3/envs/ml3105/lib/python3.10/site-packages/deepchecks/utils/abstracts/weak_segment_abstract.py:57: FutureWarning:

Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value 'Other' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.

/home/rajaraman/miniconda3/envs/ml3105/lib/python3.10/site-packages/deepchecks/tabular/checks/train_test_validation/train_test_samples_mix.py:85: FutureWarning:

DataFrame.applymap has been deprecated. Use DataFrame.map instead.

# Display and save the results
suite_result.save_as_html('titanic_analysis_report.html')
print("Deepchecks analysis report saved to 'titanic_analysis_report.html'")

Deepchecks analysis report saved to 'titanic_analysis_report.html'

# Display the results in the notebook or terminal
suite_result.show()

Accordion(children=(VBox(children=(HTML(value='\n<h1 id="summary_EKL0D0IU0T3X3W4TN4V3CMXRK">Full Suite</h1>\n<…