text: # Calculate summary statistics such as the mean, median,
  # standard deviation, and quartile information.
  # Create two new data columns for Volatility=High-Low and
  # Change=Close-Open.
  
  import pandas as pd
  
  ###Collect the data
  tableUrlSource = 'http://apmonitor.com/pds/uploads/Main/goog.txt'
  table = pd.read_csv(tableUrlSource)
  
  ###Calculate new data
  ##Volatility
  volatility = table['High'] - table['Low']
  ##Change
  change = table['Close'] - table['Open']
  ##Add the new data
  locationToInsert = 5
  table.insert(locationToInsert, "Volatility", volatility)
  table.insert(locationToInsert, "Change", change)
  
  print(table.describe())
  
  # ###Present the data
  # startColumn=1
  # endColumn=2
  # for columnLocation, columnName in zip(range(startColumn,(table.shape[1]-endColumn)),table.iloc[:,startColumn:-endColumn]):
  #     print(columnName)
  #     column = table.iloc[:,columnLocation]
  #     print(f"25%: {column.quantile(q=0.25)}")
  #     print(f"median: {column.median()}")
  #     print(f"mean: {column.mean()}")
  #     print(f"75%: {column.quantile(q=0.75)}")
  #     print(f"standard deviation: {column.std()}\n")
  