Hi I have problems with the question below:

Part 2: Functions, Derivatives, and Optimization 2.1 [1 pt] Use Sympy to make the function f = 3 In(x) + 0.01x2 - x and to take the derivative of it with respect to x. Set the variable df_dx equal to the derivative. Remember to use Sympy's In() function. In [ ]: df dx = None # YOUR CODE HERE raise NotImplementedError () In [ ]: #hidden tests for problem 2.1 are within this cell 2.2 [1 pt] Use Sympy to find the points where df_dx equals zero. Set the variable FOC_points equal to the list of those points. In [ ]: FOC_points = None # YOUR CODE HERE raise NotImplementedError () In [ ]: #hidden tests for problem 2.2 are within this cell2.3 [2 pt] Use Sympy to take take the derivative of df_dx with respect to x in order to obtain the second derivative of f with respect to x. Set the variable df_dx_2 equal to the second derivative of f with respect to x. Next, use evalf( ), subs, and list comprehension to make a list where each element is df_dx_2 evaluated at one of the elements in FOC_points (in order). Set the variable SOC_values equal to that list. In [ ]: df_dx_2 = None SOC_values = None # YOUR CODE HERE raise NotImplementedError () In [ ] : #hidden tests for problem 2.3 are within this cell 2.4 [1 pt] Finally, determine (i) whether each point in FOC_points is a local minimum or local maximum, and somehow (ii) whether each point in FOC_points that is a local minimum (maximum) is also global minimum (maximum) or not. Use list comprehension to set the variable min_or_max equal to a list where each element is either the string 'min' if the associated point in FOC_points is a local minimum or 'max' if the associated point in FOC_points is a local maximum. Set the variable global_or_not equal to a list where each element is either the string 'yes' if the associate point in FOC_points is a global extremum or 'no' otherwise. In [ ] : min_or max = None global_or_not = None # YOUR CODE HERE raise NotImplementedError() In [ ]: #hidden tests for problem 2.4 are within this cell