Community Data Science Course (Spring 2015)/Day 2 Lecture

Resources

• Python data types cheat sheet
• Python loops cheat sheet
• state_capitals.py -- the state capitals example.

Lecture outline

Review Friday 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
  • assignment of variaibles
  • 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 "concatination" (smushing things together)
  • e.g., print("Hello" + name)
  • concatenating strings and integers don't work (e.g., print(1 + "mako"))
  • 1 is different than "1"; name is different than "name"
  • single quotes versus double quotes (python doesn't care)
  • you can also multiply strings! (although it's not clear why you want to weird)
• booleans
  • comparisons (e.g., 1 == 1 or 1 == 0)
    • you can compare strings (case sensative!)
    • 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 "mako" in "makoshark"
  • e.g., adding else example: if brother_age > sister_age
  • e.g., tempreature 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!)
• functions
  • has a parentheses
  • we've already learnd examples of this: exit(), help(), type()

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 (now you understand all the zeros we've been using)
  • 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
• 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()

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 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
  • append to a list within a for loop
  • create a counter within a for loop (keep track)
  • build up a sentence
• nested for loops
• range()
• while loops
• infinite loops
• if statements inside while loops
• break
• input()

dictionaries

• purpose
• initialization
• accessing elements
• adding elements
• changing elements
• keys() and values()

modules

• purpose
• builtins
• imports
• import random
• random.randint
• random.choice

walk through state_capitals.py

Where state_capitals.py from http://mako.cc/teaching/2015/cdsw-spring/state_capitals.py is the grand finale and synthesis of lecture material.