text: from datetime import datetime, timedelta
  from airflow import DAG
  from airflow.operators.python_operator import PythonOperator
  from airflow.operators.bash_operator import BashOperator
  import pandas as pd
  
  default_args = {
      'owner': 'Caio César',
      'depends_on_past': False,
      'email': ['your_email@email.com'],
      'start_date': datetime(2020, 12, 20, 00, 00, 00),
      'email_on_failure': False,
      'email_on_retry': False,
      'retries': 1,
      'retry_delay': timedelta(minutes=2),
  }
  
  dag = DAG(
      'titanic',
      description='Mean age of titanic\'s people.',
      default_args=default_args,
      schedule_interval='*/2 * * * *',
  )
  
  get_dataset = BashOperator(
      task_id='get-data',
      bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o ~/titanic.csv',
      dag=dag
  )
  
  def calculate_mean_age():
      df = pd.read_csv('~/titanic.csv')
      med = df.Age.mean()
      return med
  
  def print_mean_age(**context):
      value = context['task_instance'].xcom_pull(task_ids='calculate-mean-age')
      print(f'Mean age: {value} years')
  
  task_mean_age = PythonOperator(
      task_id='calculate-mean-age',
      python_callable=calculate_mean_age,
      dag=dag
  )
  
  task_print_mean_age = PythonOperator(
      task_id='print-mean-age',
      python_callable=print_mean_age,
      provide_context=True,
      dag=dag
  )
  
  get_dataset >> task_mean_age >> task_print_mean_age