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

From CommunityData


Lecture outline[edit]

Review Week 1 python material[edit]

  • 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!)


  • 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()
    • e.g., reverse a list with names.reverse()
    • search "python lists" in any search engine to see many more functions that list knows about.

Optional Exercise[edit]

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

loops and more flow control[edit]

  • 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)