01.06 Jupyter Exercises 2

Exercises rating:

★☆☆ - You should be able to do it based on Python knowledge plus the text.

★★☆ - You will need to do extra thinking and some extra reading/searching.

★★★ - The answer is difficult to find by a simple search, requires you to do a considerable amount of extra work by yourself (feel free to ignore these exercises if you're short on time).

Note: Some of the exercises in this section are way beyond what we cover. Instead, the exercises are a review of your general python programming knowledge. You can safely ignore these exercises, they are not necessary for what we learn later.

1. Write a Python class that is instantiated with a list of numbers and has a .mean() method. (★☆☆)

2. Save the following into a file called by_zero.py. (★★☆)

---

def div_xy(x, y):
    return x / y

def div_by_zero(x):
    return div_xy(x, 0.0)

---

import the module and execute the div_xy function to divide 10 by 2.

P.S. You do not need to worry about an __init__.py file if the module is in the same directory.

3. What is the difference between the magic in the following cells? (★★☆)

Try to explain the differences between what you see.

%xmode Plain

by_zero.div_by_zero(3)

%xmode Context

by_zero.div_by_zero(3)

%xmode Verbose

by_zero.div_by_zero(3)

4. Use %pdb on to print out the value of y (inside div_xy) just before the division by zero. (★★★)

import by_zero
by_zero.div_by_zero(3)

5. Use %timeit to time a function that sums the elements of a list, compare it with np.sum (★★☆)

You can use np.arange(1024) to create a list of the first 1024 integers. Here is a start (this exercise ought to take a while to run):

def sums_all(l):
    pass

import numpy as np
long_list = np.arange(1024)
%timeit np.sum(long_list)
%timeit # your function

6. Use %prun to profile the function you wrote in exercise 5. (★★★)

import numpy as np
long_list = np.arange(32256)