Overview

Questions

• Practice your python.

Objectives

• Work on some python exercises to continue building your skills.

Python Practice

The key to building your skills as a programmer is practice. Try giving yourself challenges to use the Python tools we have learned in class. Here are some exercises for you to work through to continue working on becoming a Pythonista.

Python Datatypes

1. Create a list in python x = list(range(1,20)). This will make a list of numbers from 1 to 20. Now try the following with this list:
   1. Create a new list containing every 2nd element starting with element x[1].
   2. Print the last 8 values in the list to screen.
   3. Write a for loop to print each value, one at a time.
   4. Write a function that converts the entire list to a single string.
2. Create 3 dictionaries:

   d1 = {'a': 10, 'b': 20, 'c': 30}
   d1 = {'d': 40, 'e': 50}
   d1 = {'f': 60, 'g': 70, 'h': 80}
   

   1. Concatenate the dictionaries into one single dictionary called my_dictionary
   2. Check to see if my_dictionary has the key i.
   3. Change the value associated with key d to 40.4

Math

1. Use the Numpy package to draw 100 random variables from a normal distribution with mean = 5 and standard deviation = 1. Assign these to a list called norm_rvs.
2. Use Numpy to compute the sum of the list x crated in the very first exercise.
3. Write a function that takes the list norm_rvs and returns a list where each element is the log(norm_rvs[i]).
4. Use the seaborn package to view histograms of norm_rvs and the log-transformed values.

Pandas

1. Load the CSV file from our previous exercises: surveys_df = pd.read_csv("surveys.csv")
   1. Create a new dataframe variable called surveys1997 containing only the observations from the year 1997.
   2. Use a for loop to iterate over surveys1997 and print the plot number to screen.

Key Points

• Practice makes Python.