Boston Python Workshop 6/Data types

Numbers: integers and floats

 * Integers don't have a decimal place.
 * Floats have a decimal place.
 * Math mostly works the way it does on a calculator, and you can use parentheses to override the order of operations.

Math: addition, subtraction, multiplication
addition: 2 + 2

subtraction: 0 - 2

multiplication: 2 * 3

Math: division
>>> 4 / 2 2 >>> 1 / 2 0


 * Integer division produces an integer. You need a number that knows about the decimal point to get a decimal out of division:

>>> 1.0 / 2 0.5 >>> float(1) / 2 0.5

Types
>>> type(1)  >>> type(1.0) 

Strings

 * Strings are bits of text, and contain characters like numbers, letters, whitespace, and punctuation.
 * String are surrounded by quotes.
 * Use triple-quotes (""") to create whitespace-preserving multi-line strings.

>>> "Hello" 'Hello'

String concatenation
>>> "Hello" + "World" HelloWorld >>> "Hello" + "World" + 1 Traceback (most recent call last): File " ", line 1, in TypeError: cannot concatenate 'str' and 'int' objects >>> "Hello" + "World" + str(1) 'HelloWorld1'

Printing strings
>>> print "Hello" + "World" HelloWorld

>>> print """In 2009, ...    The monetary component of the Nobel Prize ...         was US $1.4 million.""" In 2009, The monetary component of the Nobel Prize was US $1.4 million.

Types
>>> type("Hello") 

Booleans

 * There are two booleans,  and.
 * Use booleans to make decisions.

Containment with 'in' and 'not in'
>>> "H" in "Hello" True >>> "a" not in ["a", "b", "c"] False

Equality

 * tests for equality
 * tests for inequality
 * ,,  , and   have the same meaning as in math class.

>>> 0 == 0 True >>> 0 == 1 False

"a" != "a"

"a" != "A"

Use with if/else blocks

 * When Python encounters the  keyword, it evaluates the expression following the keyword and before the colon. If that expression is , Python executes the code in the indented code block under the if line. If that expression is  , Python skips over the code block.

temperature = 32 if temperature > 60 and temperature < 75: print "It's nice and cozy in here!" else: print "Too extreme for me."

Types
>>> type(True)  >>> type(False) 

Lists

 * Use lists to store data where order matters.
 * Lists are indexed starting with 0.

List initialization
>>> my_list = [] >>> my_list [] >>> your_list = ["a", "b", "c", 1, 2, 3] >>> your_list ['a', 'b', 'c', 1, 2, 3]

Access and adding elements to a list
>>> len(my_list) 0 >>> my_list[0] Traceback (most recent call last): File " ", line 1, in IndexError: list index out of range >>> my_list.append("Alice") >>> my_list ['Alice'] >>> len(my_list) 1 >>> my_list[0] 'Alice' >>> my_list.insert(0, "Amy") >>> my_list ['Amy', 'Alice']

>>> my_list = ['Amy', 'Alice'] >>> 'Amy' in my_list True >>> 'Bob' in my_list False

Changing elements in a list
>>> your_list = [] >>> your_list.append("apples") >>> your_list[0] 'apples' >>> your_list[0] = "bananas" >>> your_list ['bananas']

Slicing lists
>>> her_list = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'] >>> her_list[0] 'a' >>> her_list[0:3] ['a', 'b', 'c'] >>> her_list[:3] ['a', 'b', 'c'] >>> her_list[-1] 'h' >>> her_list[5:] ['f', 'g', 'h'] >>> her_list[:] ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']

Sharing versus copying
Sharing

>>> my_list ['Alice'] >>> your_list = my_list >>> your_list ['Alice'] >>> my_list[0] = "Bob" >>> my_list ['Bob'] >>> your_list ['Bob']

Copying

>>> my_list ['Alice'] >>> your_list = my_list[:] >>> my_list[0] = "Bob" >>> my_list ['Bob'] >>> your_list ['Alice']

Strings are a lot like lists
>>> my_string = "Hello World" >>> my_string[0] 'H' >>> my_string[:5] 'Hello' >>> my_string[6:] 'World' >>> my_string = my_string[:6] + "Jessica" >>> my_string 'Hello Jessica'


 * One big way in which strings are different from lists is that lists are mutable (you can change them), and strings are immutable (you can't change them). To "change" a string you have to make a copy:

>>> h = "Hello" >>> h[0] = "J" Traceback (most recent call last): File " ", line 1, in TypeError: 'str' object does not support item assignment >>> h = "J" + h[1:] >>> h 'Jello'

Types
>>> type(my_list) 

Dictionaries

 * Use dictionaries to store key/value pairs.
 * Dictionaries do not guarantee ordering.
 * A given key can only have one value, but multiple keys can have the same value.

Initialization
>>> my_dict = {} >>> my_dict {} >>> your_dict = {"Alice" : "chocolate", "Bob" : "strawberry", "Cara" : "mint chip"} >>> your_dict {'Bob': 'strawberry', 'Cara': 'mint chip', 'Alice': 'chocolate'}

Adding elements to a dictionary
>>> your_dict["Dora"] = "vanilla" >>> your_dict {'Bob': 'strawberry', 'Cara': 'mint chip', 'Dora': 'vanilla', 'Alice': 'chocolate'}

Accessing elements of a dictionary
>>> your_dict["Alice"] 'chocolate' >>> your_dict.get("Alice") 'chocolate'

>>> your_dict["Eve"] Traceback (most recent call last): File " ", line 1, in KeyError: 'Eve' >>> "Eve" in her_dict False >>> "Alice" in her_dict True >>> your_dict.get("Eve") >>> person = your_dict.get("Eve") >>> print person None >>> print type(person)  >>> your_dict.get("Alice") 'coconut'

Changing elements of a dictionary
>>> your_dict["Alice"] = "coconut" >>> your_dict {'Bob': 'strawberry', 'Cara': 'mint chip', 'Dora': 'vanilla', 'Alice': 'coconut'}

Types
>>> type(my_dict) 

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