Community Data Science Course (Spring 2023)/Week 2 lecture notes

Resources

• Python data types cheat sheet
• Python loops cheat sheet

Lecture outline

Review Week 1 python material

• math: using python as a calculator
  • addition, subtraction, multiplication, division
  • division shows something different: 8/2 versus 2*2
• type()
  • there are different types of things in python (called objects)
  • variables that "know about the decimal place" (int) and variables that don't (floats)
  • variables that are strings.
• variables
  • assignment of variables
  • e.g., math with variables: scale up a recipe, into an assignment
  • you can assign to a variable and it will replace the old value
• strings
  • things within quotation marks
  • adding strings with "concatenation" (smushing things together)
  • e.g., print("Hello" + name)
  • concatenating strings and integers doesn't work (e.g., print(1 + "tommy"))
  • 1 is different than "1"; name is different than "name"
  • convert "1" to 1 with the int() function
  • single quotes versus double quotes (python doesn't care)
  • you can also multiply strings! (although it's not clear why you want to)
  • The type of a variable tells you what you can do with it
• Booleans
  • comparisons (e.g., 1 == 1 or 1 == 0)
    • you can compare strings (case sensitive!)
    • also >, <, and !=
  • type() shows that the output of True or False is bool
  • e.g., "i" in "team"
  • e.g., "i" not in "team"
• if/elif/else (move to external file)
  • if, something that evaluates to a Boolean, and then colon
  • e.g., if "tom" in "tommyguy"
  • e.g., adding else example: if brother_age > sister_age
  • e.g., temperature range
  • e.g., adding elif: fix the bug in the previous program if they were the same age
  • indent with spaces (we use 4 spaces!)

Lists

• purpose
  • Stores things in order
• initialization
  • making a list called my list: my_list = ["a", "b", "c"]
  • comma separated elements. in python they can be a mix of any kind of types
  • type(my_list)
• len() review
• accessing elements
  • indexing like my_list[0]
  • indexing starts from the front and we start counting at 0
  • we go from the end with negative numbers
  • what happens if we try to move outside of the range? ('error!)
• adding elements
  • using the the my_list.append() function
  • the .append() function is a special kind of function that lists know about
  • compare to print which is a global function.
• changing elements
  • replacing elements like my_list[0] = "foo"
• finding elements in list
  • e.g., "z" in my_list
• slicing lists
  • the colon inside the [] is the slicing syntax
  • e.g., my_list[0:2] is 0th up to, but not including, the 2nd
  • e.g., my_list[2:]
  • e.g., my_list[:2]
  • e.g., my_list[:]
• strings are like lists
  • we can slice lists
  • len()
    • len("") length of the empty string
• many other interesting functions for lists
  • e.g., min() and max()
  • e.g., create a list of names and sort it names.sort()
  • search "python lists" in any search engine to see many more functions that list knows about.

Exercise

Figure out what the list function pop does. Confirm with your neighbor. Write an example to be sure.

loops and more flow control

• for loops
  • e.g., for name in names: print name
  • e.g., for name in names: print 'hello ' + name
  • Super powerful because it can do something many many times. Data science is about doing tedious things very quickly. for is the workhorse that makes this possible.
  • Look and see what name is after we're done looping.
  • Move to editor.
• if statements inside for loops
  • e.g., if name[0] in "AEIOU" then print "starts with a vowel"
  • show we can test things outside the loop to show how the comparisons are working
  • add an else statement to capture words that start with a consonant
  • create a counter within a for loop (keep track)