DS4UX (Spring 2016)/Day 2 lecture: Difference between revisions
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== Part 1: Review == | == Part 1: Review == | ||
* math: using python as a calculator | * math: using python as a calculator | ||
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=== loops and more flow control === | === loops and more flow control === | ||
''See also: [[DS4UX_(Spring_2016)/Working_within_loops|working within loops]].'' | |||
* <tt>for</tt> loops | * <tt>for</tt> loops | ||
Line 101: | Line 95: | ||
* <tt>break</tt> | * <tt>break</tt> | ||
* <tt>input()</tt> | * <tt>input()</tt> | ||
=== modules === | === modules === | ||
* purpose | * purpose | ||
* builtins | * builtins | ||
* <tt>import random</tt> | * <tt>import random</tt> | ||
* <tt>random.randint</tt> | * <tt>random.randint</tt> | ||
* <tt>random.choice</tt> | * <tt>random.choice</tt> | ||
* <tt>random.sample</tt> | |||
=== walk through | === walk through favorite_buildings.py === | ||
Where <code>favorite_buildings.py</code> from http://jtmorgan.net/ds4ux/week2/others/favorite_buildings.py is the grand finale and synthesis of lecture material. | |||
[[Category:DS4UX (Spring 2016)]] | [[Category:DS4UX (Spring 2016)]] |
Latest revision as of 22:35, 4 April 2016
Part 1: Review[edit]
- math: using python as a calculator
- addition, subtraction, multiplication, division
- division shows something different:
8/2
versus2*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
or1 == 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"
- comparisons (e.g.,
- 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., temperature range (e.g., if temp<65 is cold; temp>80 is hot; otherwise, just right)
- 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()
Part 2: New programming concepts[edit]
Lists[edit]
- 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)
- making a list called 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
- using the the
- changing elements
- replacing elements like
my_list[0] = "foo"
- replacing elements like
- finding elements in list
- e.g.,
"z" in my_list
- e.g.,
- 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()
andmax()
- e.g., create a list of names and sort it
names.sort()
- e.g.,
loops and more flow control[edit]
See also: working within loops.
- 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.
- e.g.,
- 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
- e.g.,
- nested for loops
- range()
- while loops
- infinite loops
- if statements inside while loops
- break
- input()
modules[edit]
- purpose
- builtins
- import random
- random.randint
- random.choice
- random.sample
walk through favorite_buildings.py[edit]
Where favorite_buildings.py
from http://jtmorgan.net/ds4ux/week2/others/favorite_buildings.py is the grand finale and synthesis of lecture material.