text: import pandas as pd
  import numpy as np
  
  data = {'ReleaseYear': [2009, 2019, 2015, 2013, 2005],
          'Movie': ["Avatar", "Avengers:Endgame", "Star Wars Ep VII: The Force Awakens"]
          'Expense':[328262000, 475560000, 381704000, 245904000, 208064000]
          'Profit': [1499182307, 1010189087, 843123707, 797747501, 789505652]}
  
  
  
  pd.set_option('display.max_columns', None)
  df = pd.DataFrame(data)
  
  #multiple column selection
  print(df[['Expense', 'Profit']])
  print(df.loc[:, [['Expense', 'Profit']]])
  print(df.loc[:, ['Expense', 'Profit']])
  print(df.iloc[:, [2,3]])
  print(df.iloc[:, 2:4])
  
  
  
  
  # row filtering: ReleaseYear >= 2010
  print(df['ReleaseYear'] >= 2010)
  print(df.ReleaseYear >= 2010)
  
  #Other ones
  
  dfFil = df[df.ReleaseYear >= 2010]
  print(dfFil[:, [['Expense', 'Profit']]])
  print(dfFil.loc[:, ['Expense', 'Profit']])
  
  
  #calculate
  print(df['Profit'] / 1000000)
  
  #calculate the age of each movie
  
  #calculate expense as a percentage of profit
  print(df['Expense']/df['Profit'])
  print(df.Expense / df.Profit)
  
  #modifying DataFrames
  df['Ones'] = 1
  print(df)
  
  dfCheap = df[df.Expense / df.Profit < 0.30]
  print(dfCheap.Movie)