title: exporting Python model results
body: <p>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?  </p>
  
  <pre><code># 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)
  </code></pre>