input: Write a script in Python to compete in a Kaggle competition. The script should include loading necessary libraries, reading in the data, splitting the data into predictors and response, performing train-test split, defining a model, fitting the model, making predictions, scoring the predictions, and submitting the predictions to Kaggle. If the data file is not found, the script should return an appropriate error message.
  assert kaggle_competition_script()=="Data file not found."
  assert kaggle_competition_script()=="Competition submission successful."
output: def kaggle_competition_script():
      try:
          import pandas as pd
          from sklearn.model_selection import train_test_split
          from sklearn.ensemble import RandomForestRegressor
          from sklearn.metrics import mean_squared_error
  
          data = pd.read_csv('data.csv')
          X = data.drop('target', axis=1)
          y = data['target']
          X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
          model = RandomForestRegressor(random_state=42)
          model.fit(X_train, y_train)
  
          predictions = model.predict(X_test)
          score = mean_squared_error(y_test, predictions)
  
          submission = pd.DataFrame({'Id': X_test.index, 'Predicted': predictions})
          submission.to_csv('submission.csv', index=False)
  
          return "Competition submission successful."
      except FileNotFoundError:
          return "Data file not found."