Topics for the Midterm

Week 1 Introduction to Python

Learning objectives: You will learn to:

• Identify and describe values of different types in Python code

• Perform simple computations on these values

• Store values and the results of computations in variables

• Using built in functions

• Run Python code and display results in a Jupyter notebook (like this one!)

Week 2 Strings, lists, conditionals and Loops

You will be able to:

• Use a variety of string methods

  • str.upper()

  • str.lower()

  • str.replace(old, new)

  • str.split()

• Explain the difference between a function and a method

• Write code using the list type

• Use conditional statements (if statements) to control how Python is executed

• Use loops, specifically for loops to repeat operations multiple times.

Week 3: Reading files, dictionaries, central tendency measures

You will learn to:

• read csv files

• store data from a file into a list

• use a new data type called a dictionary that stores key, value pairs

• explain and compute central tendency statistics

• summarize survey data using dictionaries and basic python

Week 4: Introduction to Pandas and Data Wrangling

• Introduction to working with (tabular) data using pandas

• Learn about the two key data structures in pandas:

  • Series (1-dimensional)

  • DataFrame (2-dimensional).

• Import a csv file into a pandas DataFrame

• Selecting rows of a DataFrame using Boolean Series

• Selecting columns of a DataFrame

• Computing summary statistics on a DataFrame

• Discuss some features the cencus and the kinds of data Stats Canada collects

• Begin to use strategies to “clean” the data before computing various statistics on it.

Week 5: Data transformations

• Create a new column based on the values from another column

• Rename columns

• Replace missing value codes with np.nan

• Describe the differences between categorical and quantitative data

For this test, you will not be asked to

• use .groupby()

• use .loc()

• produce a box plot