text: import pandas as pd
  import sys
  
  # The score dataframe (.csv) has to be passed as an argument while executing Easy_grading.py
  second_argument = sys.argv[1]
  
  # Load csv score dataframe
  score_df = pd.read_csv(second_argument)
  
  # Function for the user inputs
  def user_input(colname):
      column_use = input("Do you want to calculate grades for " + colname + "? (y/n)")
      if column_use.lower() == 'y' or column_use.lower() == 'yes':
          max_score = int(input("What is the maximum score for this test?"))
          percentage = int(input("What is the minimum score percentage (just the number) for approval? (60% or 50% are commonly used)"))
      else:
          print("Let's skip the column then")
          max_score = 0
          percentage = 0
      return max_score, percentage
  
  
  # Function that calculates the grade for each score
  def grade_calculator(score, max_score, percentage):
      min_grade = 1.0
      max_grade = 7.0
      approval_grade = 4.0
      e = percentage/100
      if score < e * max_score:
          grade = (approval_grade - min_grade) * (score / (e * max_score)) + min_grade
      elif score >= e * max_score:
          grade = (max_grade - approval_grade) * ((score - e * max_score) / (max_score * (1 - e))) + approval_grade
      else:
          print("Something went wrong, try again")
      return (round(grade,2))
  
  # Iterates through the desired columns with user_input() and apply grade_calculator()
  for i in range(1,len(score_df.columns)):
      max_score, percentage = user_input(score_df.columns[i])
      if not (max_score == 0) and not (percentage == 0):
          score_df['Grade of ' + score_df.columns[i]] = score_df[score_df.columns[i]].apply(grade_calculator, args = (max_score, percentage))
  
  # Saves grades to a csv file
  score_df.to_csv("sample_grades_output_data.csv", index = False)
  