exporting Python model results
Question: Hi I’ve launched a random forest over a dataset imported as df. Now I would
like to export both results (0-1 prediction) and predicted probabilities ( a
two dimensions array) and match them to my dataset df. Is that possible? Until
now I figured out how to export in a separate way to csv. And yes, I am not a
pandas expert yet. Any hint?

    
    
    # Import the `RandomForestClassifier`
    from sklearn.ensemble import RandomForestClassifier
    
    
    # Create the target and features numpy arrays: 
    
    target = df["target"].values
    
    
    features =df[["var1",
    "var2","var3","var4","var5"]]
    
    
    features_forest = features
    
    # Building and fitting my_forest
    forest = RandomForestClassifier(max_depth = 10, min_samples_split=2, n_estimators = 200, random_state = 1)
    my_forest = forest.fit(features_forest, target)
    
    # Print the score of the fitted random forest
    print(my_forest.score(features_forest, target))
    
    
    print(my_forest.feature_importances_)
    
    
    results = my_forest.predict(features)
    
    print(results)
    
    predicted_probs = forest.predict_proba(features)
    
    #predicted_probs = my_forest.predict_proba(features)
    
    print(predicted_probs)
    
    id_test = df['ID_CONTACT']
    
    
    pd.DataFrame({"id": id_test, "relevance": results, "probs": predicted_probs }).to_csv('C:\Users\me\Desktop\python\data\submission.csv',index=False)
    
    
    pd.DataFrame(predicted_probs).to_csv('C:\Users\me\Desktop\python\data\submission_2.csv',index=False)
    


Answer: You should be able to

    
    
    df['results] = results
    df = pd.concat([df, pd.DataFrame(predicted_probs, columns=['Col_1', 'Col_2'])], axis=1)
    

