figure comparing the performance of pop and pop( pz pop_zero timeit(number= print("% % %(pz,pt)figure shows the results of our experiment you can see that as the list gets longer and longer the time it takes to pop( also increases while the time for pop stays very flat this is exactly what we would expect to see for (nand ( algorithm some sources of error in our little experiment include the fact that there are other processes running on the computer as we measure that may slow down our codeso even though we try to minimize other things happening on the computer there is bound to be some variation in time that is why the loop runs the test one thousand times in the first place to statistically gather enough information to make the measurement reliable dictionaries the second major python data structure is the dictionary as you probably recalldictionaries differ from lists in that you can access items in dictionary by key rather than position later in this book you will see that there are many ways to implement dictionary the thing that is most important to notice right now is that the get item and set item operations on dictionary are ( another important dictionary operation is the contains operation checking to see whether key is in the dictionary or not is also ( the efficiency of all dictionary operations algorithm analysis