Difference between revisions of "EGR 103/Concept List/S23"
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** Includes links to Sakai, Pundit, and Ed pages | ** Includes links to Sakai, Pundit, and Ed pages | ||
* Sakai page: [https://sakai.duke.edu/portal/site/egr103s23 Sakai 103L page]; grades, surveys and tests, some assignment submissions; first day slideshow in Resources section goes over everything else. | * Sakai page: [https://sakai.duke.edu/portal/site/egr103s23 Sakai 103L page]; grades, surveys and tests, some assignment submissions; first day slideshow in Resources section goes over everything else. | ||
− | == Lecture 2 - | + | == Lecture 2 - 1/13 - Programs and Programming == |
* Almost all languages have input, output, math, conditional execution (decisions), and repetition (loops) | * Almost all languages have input, output, math, conditional execution (decisions), and repetition (loops) | ||
* Seven steps of programming [https://adhilton.pratt.duke.edu/sites/adhilton.pratt.duke.edu/files/u37/iticse-7steps.pdf The Seven Steps Poster]. Also, for next Friday's class: | * Seven steps of programming [https://adhilton.pratt.duke.edu/sites/adhilton.pratt.duke.edu/files/u37/iticse-7steps.pdf The Seven Steps Poster]. Also, for next Friday's class: | ||
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** See if number is evenly divisible by any integer between 2 and the square root of the number - but how do we ask the ''computer'' to do that? | ** See if number is evenly divisible by any integer between 2 and the square root of the number - but how do we ask the ''computer'' to do that? | ||
* Very quick tour of Python with Spyder | * Very quick tour of Python with Spyder | ||
+ | ** Console (with history tab), variable explorer (with other tabs), and editing window | ||
− | + | == Lecture 3 - 1/13 - "Number" Types == | |
− | == Lecture 3 - | + | * Google Colab notebook available in the [https://drive.google.com/drive/folders/1_RM9uyvXuktDj_QuU3Gwc2tUUKB80rbL?usp=share_link EGR 103 Google Drive folder] |
− | * | ||
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
* Comments in code: | * Comments in code: | ||
** If there is a <code>#</code>, Python ignores everything remaining in that line after the # | ** If there is a <code>#</code>, Python ignores everything remaining in that line after the # | ||
Line 28: | Line 22: | ||
* Python is a "typed" language | * Python is a "typed" language | ||
** Focus of the day: int, float, and array | ** Focus of the day: int, float, and array | ||
− | *** int: integers; Python 3 can store these perfectly | + | *** int: integers; Python 3 can store these perfectly up to ginormous sizes |
*** float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly | *** float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly | ||
− | + | * Basic operations for ints and floats | |
− | |||
− | |||
− | * Basic operations and | ||
** + - * // (rounded division) and % (remainder / modulo) produce int if both sides are an int, float if either or both are floats | ** + - * // (rounded division) and % (remainder / modulo) produce int if both sides are an int, float if either or both are floats | ||
− | ** / (regular | + | ** / (regular division) produces float with ints or floats |
** ** to do powers | ** ** to do powers | ||
− | ** <code> | + | ** Relational operators can compare "Number" Types and work the way you expect with <code>True</code> or <code>False</code> as an answer |
+ | *** < <= == >= > != | ||
+ | ** Logical operators can combine (<code>and</code>, <code>or</code>) booleans or reverse (<code> not</code>) | ||
+ | * You can convert strings containing characters that "look" like numbers to ints or floats: | ||
** <code>NUM = int(VAR)</code> | ** <code>NUM = int(VAR)</code> | ||
*** If VAR is an int or a float, it will return an int rounded towards 0 | *** If VAR is an int or a float, it will return an int rounded towards 0 | ||
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*** If VAR is an int or a float, it will return a float with the same value | *** If VAR is an int or a float, it will return a float with the same value | ||
*** If VAR is a string, it will return a float if the string looks like a float, including scientific notation such as <code>float("1.23e4")</code> | *** If VAR is a string, it will return a float if the string looks like a float, including scientific notation such as <code>float("1.23e4")</code> | ||
+ | ** This is important because <code>VAR = input("prompt: ")</code> will ask the user for a value and stores whatever they type as a '''string''' | ||
* Arrays | * Arrays | ||
− | ** Python doesn't know everything to start with; may need to import things | + | ** Python doesn't know everything to start with; may need to import things - must import numpy for arrays |
*** <code>import MODULE</code> means using <code>MODULE.function()</code> to run | *** <code>import MODULE</code> means using <code>MODULE.function()</code> to run | ||
− | *** <code>import MODULE as NAME</code> means using <code>NAME.function()</code> to run | + | *** <code>import MODULE as NAME</code> means using <code>NAME.function()</code> to run - this is the most common one for us |
+ | *** <code> from MODULE import FUNCTION1, FUNCTION2, ...</code> means using FUNCTION1(), FUNCTION2() as function calls - be careful not to override things | ||
+ | *** <code> from MODULE import *</code> means importing every function and constant from a module into their own name - very dangerous! | ||
+ | ** <code>import numpy as np</code> will be a very common part of code for EGR 103 | ||
** Organizational unit for storing rectangular arrays of numbers | ** Organizational unit for storing rectangular arrays of numbers | ||
** Generally create with np.array(LIST) where depth of nested LIST is dimensionality of array | ** Generally create with np.array(LIST) where depth of nested LIST is dimensionality of array | ||
*** np.array([1, 2, 3]) is a 1-dimensional array with 3 elements | *** np.array([1, 2, 3]) is a 1-dimensional array with 3 elements | ||
*** np.array([[1, 2, 3], [4, 5, 6]]) is a 2-dimension array with 2 rows and 3 columns | *** np.array([[1, 2, 3], [4, 5, 6]]) is a 2-dimension array with 2 rows and 3 columns | ||
− | * Math with | + | ** Math with arrays works the way you expect |
− | ** ** * / // % + - | + | *** ** * / // % + - |
− | ** With arrays, * and / work element by element; *matrix* multiplication is a different character (specifically, @) | + | **** With arrays, * and / work element by element; *matrix* multiplication is a different character (specifically, @) |
− | * Relational operators can compare | + | ** Relational operators can compare two arrays that are the same size or an array and a single number |
− | ** < <= == >= > != | + | *** < <= == >= > != |
− | ** With arrays, either same size or one is a single value; result will be an array of True and False the same size as the array | + | *** With arrays, either same size or one is a single value; the result will be an array of True and False the same size as the array |
− | * Slices allow us to extract information from a collection or change information in mutable collections | + | ** Slices allow us to extract information from a collection or change information in mutable collections |
− | * a[0] is the element in a at the start | + | *** a[0] is the element in a at the start |
− | * a[3] is the element in a three away from the start | + | *** a[3] is the element in a three away from the start |
− | * a[-1] is the last element of a | + | *** a[-1] is the last element of a |
− | * a[-2] is the second-to-last element of a | + | *** a[-2] is the second-to-last element of a |
− | * a[:] is all the elements in a because what is really happening is: | + | *** a[:] is all the elements in a because what is really happening is: |
− | ** a[start:until] where start is the first index and until is just *past* the last index; | + | **** a[start:until] where start is the first index and until is just *past* the last index; |
− | ** a[3:7] will return a[3] through a[6] in a 4-element array | + | **** a[3:7] will return a[3] through a[6] in a 4-element array |
− | ** a[start:until:increment] will skip indices by increment instead of 1 | + | **** a[start:until:increment] will skip indices by increment instead of 1 |
− | ** To go backwards, a[start:until:-increment] will start at an index and then go backwards until getting at or just past until. | + | **** To go backwards, a[start:until:-increment] will start at an index and then go backwards until getting at or just past until. |
− | * For 2-D arrays, you can index items with either separate row and column indices or indices separated by commas: | + | ** For 2-D arrays, you can index items with either separate row and column indices or indices separated by commas: |
− | ** a[2][3] is the same as a[2, 3] | + | *** a[2][3] is the same as a[2, 3] |
− | ** Only works for arrays! | + | *** Only works for arrays! |
− | == Lecture 4 - | + | == Lecture 4 - 1/23 - List, Tuple String == |
+ | * Google Colab notebook available in the [https://drive.google.com/drive/folders/1_RM9uyvXuktDj_QuU3Gwc2tUUKB80rbL?usp=share_link EGR 103 Google Drive folder] | ||
+ | * Python script available in the [ | ||
* Lists are set off with [ ] and entries can be any valid type (including other lists!); entries can be of different types from other entries; list items can be changed and mutable items within lists can be changed. Lists can be "grown" by using += with the list or l.append(). | * Lists are set off with [ ] and entries can be any valid type (including other lists!); entries can be of different types from other entries; list items can be changed and mutable items within lists can be changed. Lists can be "grown" by using += with the list or l.append(). | ||
* Tuples are indicated by commas without square brackets (and are usually shown with parentheses - which are required if trying to make a tuple an entry in a tuple or a list); tuple items cannot be changed but mutable items within tuples can be | * Tuples are indicated by commas without square brackets (and are usually shown with parentheses - which are required if trying to make a tuple an entry in a tuple or a list); tuple items cannot be changed but mutable items within tuples can be | ||
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** [https://www.tutorialspoint.com/python/python_lists.htm Lists] at tutorialspoint | ** [https://www.tutorialspoint.com/python/python_lists.htm Lists] at tutorialspoint | ||
** [https://www.tutorialspoint.com/python/python_tuples.htm Tuples] at tutorialspoint | ** [https://www.tutorialspoint.com/python/python_tuples.htm Tuples] at tutorialspoint | ||
+ | |||
+ | == Lecture 5 - 1/27 - Formatted Printing; Functions== | ||
+ | * Google Colab notebook available in the [https://drive.google.com/drive/folders/1_RM9uyvXuktDj_QuU3Gwc2tUUKB80rbL?usp=share_link EGR 103 Google Drive folder] | ||
* Creating formatted strings using {} and .format() ([https://www.python.org/dev/peps/pep-3101/#format-strings format strings], [https://www.python.org/dev/peps/pep-3101/#standard-format-specifiers standard format specifiers]) -- focus was on using s for string and e or f for numerical types, minimumwidth.precision, and possibly a + in front to force printing + for positive numbers. | * Creating formatted strings using {} and .format() ([https://www.python.org/dev/peps/pep-3101/#format-strings format strings], [https://www.python.org/dev/peps/pep-3101/#standard-format-specifiers standard format specifiers]) -- focus was on using s for string and e or f for numerical types, minimumwidth.precision, and possibly a + in front to force printing + for positive numbers. | ||
** Using {} by themselves will substitute items in order from the <code>format()</code> function into the string that gets created | ** Using {} by themselves will substitute items in order from the <code>format()</code> function into the string that gets created | ||
** Putting a number in the {} will tell <code>format</code> which thing to get | ** Putting a number in the {} will tell <code>format</code> which thing to get | ||
** Format specification comes after a : in the {}; if you do not specify a location index, you still have to put a colon in the {} | ** Format specification comes after a : in the {}; if you do not specify a location index, you still have to put a colon in the {} | ||
− | ** {:s} means string and {:Xs} where X is an integer means reserve at least that much space for a left-formatted string | + | *** {:s} means string and {:Xs} where X is an integer means reserve at least that much space for a left-formatted string; {:>s} or {:>Xs} where X is a number will right-justify the string |
− | ** {:f} means floating point (default 6 digits after decimal point) and {:X.Yf} reserves at least X spaces (including + or - and the . if it is there) with Y digits after the decimal point for t '''right'''-justified number | + | *** {:f} means floating point (default 6 digits after decimal point) and {:X.Yf} reserves at least X spaces (including + or - and the . if it is there) with Y digits after the decimal point for t '''right'''-justified number |
− | ** {:e} means floating point (default 6 digits after decimal point) and {:X.Ye} reserves at least X spaces (including + or - and the . if it is there and the letter e and the + or - after the e and the two or three digit number after that) with Y digits after the decimal point for t '''right'''-justified number | + | *** {:e} means floating point (default 6 digits after decimal point) and {:X.Ye} reserves at least X spaces (including + or - and the . if it is there and the letter e and the + or - after the e and the two or three digit number after that) with Y digits after the decimal point for t '''right'''-justified number |
− | * Aside - [https://docs.python.org/3/library/string.html#format-specification-mini-language Format Specification Mini-Language] has all the possibilities; we will cover some but not all of these in later classes | + | ** Aside - [https://docs.python.org/3/library/string.html#format-specification-mini-language Format Specification Mini-Language] has all the possibilities; we will cover some but not all of these in later classes |
− | * You can enter numbers in scientific notation with a number followed by the letter 3 and then a number or negative number for the power of 10; for example, <code>x = 6.02e23</code> or <code>e = -1.6e-19</code> | + | ** You can enter numbers in scientific notation with a number followed by the letter 3 and then a number or negative number for the power of 10; for example, <code>x = 6.02e23</code> or <code>e = -1.6e-19</code> |
** float can convert scientific notation as well: | ** float can convert scientific notation as well: | ||
float("1e-5") | float("1e-5") | ||
− | + | * Lambda functions can have multiple arguments but can perform only one calculation and will return the result of that one calculation: <syntaxhighlight lang=python>fun_name = lambda in_1, in_2, in_3, in_4: CALCULATION</syntaxhighlight> | |
− | == | + | ** For example:<syntaxhighlight lang=python>hyp = lambda a, b: np.sqrt(a**2 + b**2)</syntaxhighlight> |
− | * | + | * Formally defined functions can be multiple lines of code and have multiple outputs. |
− | * The function can see everything in main, but main cannot see things created in the function. | + | ** The function can see everything in main, but main cannot see things created in the function. |
− | ** Best bet is to pretend the function cannot see things in main - pass everything in that you need to see! | + | *** Best bet is to pretend the function cannot see things in main - pass everything in that you need to see! |
− | *<syntaxhighlight lang=python> | + | **<syntaxhighlight lang=python> |
def FNAME(local1, local2, ...): | def FNAME(local1, local2, ...): | ||
CODE | CODE | ||
Line 123: | Line 126: | ||
**** Function will create a tuple containing these items in order | **** Function will create a tuple containing these items in order | ||
*** Additional keyword arguments ("**kwargs") (last) | *** Additional keyword arguments ("**kwargs") (last) | ||
− | **** Function will create a dictionary of keyword and value pairs | + | **** Function will create a '''dictionary''' of keyword and value pairs -more about dictionaries later |
** Function ends when indentation stops or when the function hits a return statement | ** Function ends when indentation stops or when the function hits a return statement | ||
** Return returns single item as an item of that type; if there are multiple items returned, they are stored and returned in a tuple | ** Return returns single item as an item of that type; if there are multiple items returned, they are stored and returned in a tuple | ||
** If there is a left side to the function call, it either needs to be a single variable name or a tuple with as many entries as the number of items returned | ** If there is a left side to the function call, it either needs to be a single variable name or a tuple with as many entries as the number of items returned | ||
− | |||
− | |||
− | == Lecture 6 - | + | == Lecture 6 - 1/30 - Loops and Decisions == |
− | * | + | * Google Colab notebook available in the [https://drive.google.com/drive/folders/1_RM9uyvXuktDj_QuU3Gwc2tUUKB80rbL?usp=share_link EGR 103 Google Drive folder] |
* Logic | * Logic | ||
** <= < == >= > != work with many types; just be careful about interpreting | ** <= < == >= > != work with many types; just be careful about interpreting | ||
** <code>not</code> can reverse while <code>and</code> and <code>or</code> can combine logical expressions; most expressions can be written in two ways (while/if TRUE or while/if not FALSE) | ** <code>not</code> can reverse while <code>and</code> and <code>or</code> can combine logical expressions; most expressions can be written in two ways (while/if TRUE or while/if not FALSE) | ||
+ | ** in can ask if a character / substring is in a string or if an element is in a list or tuple | ||
* Basics of decisions using if...elif...else | * Basics of decisions using if...elif...else | ||
** Must have logic after if | ** Must have logic after if | ||
Line 153: | Line 155: | ||
**** range only creates integers | **** range only creates integers | ||
− | == Lecture 7 - | + | == Lecture 7 - 2/3 - Loops and Accounting == |
+ | * The Price is Right! | ||
* Looked at looping through letters in a phrase | * Looked at looping through letters in a phrase | ||
* Logic: ITEM in THING will be true if ITEM is a subunit of THING | * Logic: ITEM in THING will be true if ITEM is a subunit of THING | ||
Line 166: | Line 169: | ||
** For loop with another for loop | ** For loop with another for loop | ||
− | == Lecture 8 - | + | == Lecture 8 - 2/6 - Dictionaries == |
* Dictionaries are collections of key : value pairs set off with { }; keys can be any immutable type (int, float, string, tuple) and must be unique; values can be any type and do not need to be unique | * Dictionaries are collections of key : value pairs set off with { }; keys can be any immutable type (int, float, string, tuple) and must be unique; values can be any type and do not need to be unique | ||
** [https://www.tutorialspoint.com/python/python_dictionary.htm Dictionary] at tutorialspoint | ** [https://www.tutorialspoint.com/python/python_dictionary.htm Dictionary] at tutorialspoint | ||
Line 175: | Line 178: | ||
** Loading lines of text from a file | ** Loading lines of text from a file | ||
** Splitting strings with split | ** Splitting strings with split | ||
+ | <!-- | ||
* Don't copy code from a PDF! | * Don't copy code from a PDF! | ||
** waffle versus waffle versus waffle | ** waffle versus waffle versus waffle | ||
*** <code>waffle versus waffle versus waffle</code> | *** <code>waffle versus waffle versus waffle</code> | ||
** In the first version, the f-f-l are three separate characters, in the second version it is ff-l and in the third, it is ffl; if you try to copy/paste these into Spyder, the words are 6, 5, or 4 characters, respectively! | ** In the first version, the f-f-l are three separate characters, in the second version it is ff-l and in the third, it is ffl; if you try to copy/paste these into Spyder, the words are 6, 5, or 4 characters, respectively! | ||
− | + | --> | |
+ | <!-- | ||
== Lecture 9 - 9/26 - Random Numbers and Logical Masks == | == Lecture 9 - 9/26 - Random Numbers and Logical Masks == | ||
* np.random.randint(low, high, size) | * np.random.randint(low, high, size) |
Latest revision as of 03:00, 9 February 2023
Contents
- 1 Lecture 1 - 1/11 - Course Introduction
- 2 Lecture 2 - 1/13 - Programs and Programming
- 3 Lecture 3 - 1/13 - "Number" Types
- 4 Lecture 4 - 1/23 - List, Tuple String
- 5 Lecture 5 - 1/27 - Formatted Printing; Functions
- 6 Lecture 6 - 1/30 - Loops and Decisions
- 7 Lecture 7 - 2/3 - Loops and Accounting
- 8 Lecture 8 - 2/6 - Dictionaries
Lecture 1 - 1/11 - Course Introduction
- Main class page: EGR 103L
- Includes links to Sakai, Pundit, and Ed pages
- Sakai page: Sakai 103L page; grades, surveys and tests, some assignment submissions; first day slideshow in Resources section goes over everything else.
Lecture 2 - 1/13 - Programs and Programming
- Almost all languages have input, output, math, conditional execution (decisions), and repetition (loops)
- Seven steps of programming The Seven Steps Poster. Also, for next Friday's class:
- Watch video on Developing an Algorithm
- Watch video on A Seven Step Approach to Solving Programming Problems
- Problem: Consider how to decide if a number is a prime number
- Some "shortcuts" for specific factors (2, 3, and 5, for example) but need to have a generalized approach
- See if number is evenly divisible by any integer between 2 and the square root of the number - but how do we ask the computer to do that?
- Very quick tour of Python with Spyder
- Console (with history tab), variable explorer (with other tabs), and editing window
Lecture 3 - 1/13 - "Number" Types
- Google Colab notebook available in the EGR 103 Google Drive folder
- Comments in code:
- If there is a
#
, Python ignores everything remaining in that line after the # - If there are
"""
or, Python ignores everything until the closing
"""
or - If you use
# %%
in Spyder, the editing window will set up a cell and light up the cell your cursor is in. Cells have no impact on how the code runs, just how the code appears in the window
- If there is a
- Python is a "typed" language
- Focus of the day: int, float, and array
- int: integers; Python 3 can store these perfectly up to ginormous sizes
- float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly
- Focus of the day: int, float, and array
- Basic operations for ints and floats
- + - * // (rounded division) and % (remainder / modulo) produce int if both sides are an int, float if either or both are floats
- / (regular division) produces float with ints or floats
- ** to do powers
- Relational operators can compare "Number" Types and work the way you expect with
True
orFalse
as an answer- < <= == >= > !=
- Logical operators can combine (
and
,or
) booleans or reverse (not
)
- You can convert strings containing characters that "look" like numbers to ints or floats:
NUM = int(VAR)
- If VAR is an int or a float, it will return an int rounded towards 0
- If VAR is a string, it will return an int only if the string looks exactly like an integer
NUM = float(VAR)
- If VAR is an int or a float, it will return a float with the same value
- If VAR is a string, it will return a float if the string looks like a float, including scientific notation such as
float("1.23e4")
- This is important because
VAR = input("prompt: ")
will ask the user for a value and stores whatever they type as a string
- Arrays
- Python doesn't know everything to start with; may need to import things - must import numpy for arrays
import MODULE
means usingMODULE.function()
to runimport MODULE as NAME
means usingNAME.function()
to run - this is the most common one for usfrom MODULE import FUNCTION1, FUNCTION2, ...
means using FUNCTION1(), FUNCTION2() as function calls - be careful not to override thingsfrom MODULE import *
means importing every function and constant from a module into their own name - very dangerous!
import numpy as np
will be a very common part of code for EGR 103- Organizational unit for storing rectangular arrays of numbers
- Generally create with np.array(LIST) where depth of nested LIST is dimensionality of array
- np.array([1, 2, 3]) is a 1-dimensional array with 3 elements
- np.array([[1, 2, 3], [4, 5, 6]]) is a 2-dimension array with 2 rows and 3 columns
- Math with arrays works the way you expect
- ** * / // % + -
- With arrays, * and / work element by element; *matrix* multiplication is a different character (specifically, @)
- ** * / // % + -
- Relational operators can compare two arrays that are the same size or an array and a single number
- < <= == >= > !=
- With arrays, either same size or one is a single value; the result will be an array of True and False the same size as the array
- Slices allow us to extract information from a collection or change information in mutable collections
- a[0] is the element in a at the start
- a[3] is the element in a three away from the start
- a[-1] is the last element of a
- a[-2] is the second-to-last element of a
- a[:] is all the elements in a because what is really happening is:
- a[start:until] where start is the first index and until is just *past* the last index;
- a[3:7] will return a[3] through a[6] in a 4-element array
- a[start:until:increment] will skip indices by increment instead of 1
- To go backwards, a[start:until:-increment] will start at an index and then go backwards until getting at or just past until.
- For 2-D arrays, you can index items with either separate row and column indices or indices separated by commas:
- a[2][3] is the same as a[2, 3]
- Only works for arrays!
- Python doesn't know everything to start with; may need to import things - must import numpy for arrays
Lecture 4 - 1/23 - List, Tuple String
- Google Colab notebook available in the EGR 103 Google Drive folder
- Python script available in the [
- Lists are set off with [ ] and entries can be any valid type (including other lists!); entries can be of different types from other entries; list items can be changed and mutable items within lists can be changed. Lists can be "grown" by using += with the list or l.append().
- Tuples are indicated by commas without square brackets (and are usually shown with parentheses - which are required if trying to make a tuple an entry in a tuple or a list); tuple items cannot be changed but mutable items within tuples can be
- Strings are set off with " " or ' ' and contain characters; string items cannot be changed
- For lists, tuples, and strings:
- Using + concatenates the two collections
- Using * with them makes creates a collection with the original repeated that many times
- Using += will create a new item with something appended to the old item; the "something" needs to be the same type (list, tuple, or string); this may seem to break the "can't be changed" rule but really
a += b
isa = a + b
which creates a newa
.
- Characters in strings have "numerical" values based on the ASCII table (https://www.asciitable.com/)
- Numbers are earlier than lower case letters; lower case letters are earlier than upper case letters
- Strings are sorted character by character; if one string is shorter than another, it is considered less
- " Hello" < "Hi" is True since the "e" comes before the "i"
- "Zebra" < "apple" is True since the upper case "Z" is before the lower case "a"
- "go" < "gone" is True since the first two characters match and then the word is done
- To get the numerical value of a single character, use
ord("A")
or replace the A with the character you want - To get the character a number represents, use
chr(NUM)
- To apply either ord or chr to multiple items, use a
map
; to see the results, make alist
out of the map - Trinket
- To read more:
Lecture 5 - 1/27 - Formatted Printing; Functions
- Google Colab notebook available in the EGR 103 Google Drive folder
- Creating formatted strings using {} and .format() (format strings, standard format specifiers) -- focus was on using s for string and e or f for numerical types, minimumwidth.precision, and possibly a + in front to force printing + for positive numbers.
- Using {} by themselves will substitute items in order from the
format()
function into the string that gets created - Putting a number in the {} will tell
format
which thing to get - Format specification comes after a : in the {}; if you do not specify a location index, you still have to put a colon in the {}
- {:s} means string and {:Xs} where X is an integer means reserve at least that much space for a left-formatted string; {:>s} or {:>Xs} where X is a number will right-justify the string
- {:f} means floating point (default 6 digits after decimal point) and {:X.Yf} reserves at least X spaces (including + or - and the . if it is there) with Y digits after the decimal point for t right-justified number
- {:e} means floating point (default 6 digits after decimal point) and {:X.Ye} reserves at least X spaces (including + or - and the . if it is there and the letter e and the + or - after the e and the two or three digit number after that) with Y digits after the decimal point for t right-justified number
- Aside - Format Specification Mini-Language has all the possibilities; we will cover some but not all of these in later classes
- You can enter numbers in scientific notation with a number followed by the letter 3 and then a number or negative number for the power of 10; for example,
x = 6.02e23
ore = -1.6e-19
- float can convert scientific notation as well:
- Using {} by themselves will substitute items in order from the
float("1e-5")
- Lambda functions can have multiple arguments but can perform only one calculation and will return the result of that one calculation:
fun_name = lambda in_1, in_2, in_3, in_4: CALCULATION
- For example:
hyp = lambda a, b: np.sqrt(a**2 + b**2)
- For example:
- Formally defined functions can be multiple lines of code and have multiple outputs.
- The function can see everything in main, but main cannot see things created in the function.
- Best bet is to pretend the function cannot see things in main - pass everything in that you need to see!
def FNAME(local1, local2, ...): CODE return THING1, THING2, ...
- Four different types of input parameters - we only really talked about the first three kinds:
- Required (listed first)
- Named with defaults (second)
- Additional positional arguments ("*args") (third)
- Function will create a tuple containing these items in order
- Additional keyword arguments ("**kwargs") (last)
- Function will create a dictionary of keyword and value pairs -more about dictionaries later
- Function ends when indentation stops or when the function hits a return statement
- Return returns single item as an item of that type; if there are multiple items returned, they are stored and returned in a tuple
- If there is a left side to the function call, it either needs to be a single variable name or a tuple with as many entries as the number of items returned
- The function can see everything in main, but main cannot see things created in the function.
Lecture 6 - 1/30 - Loops and Decisions
- Google Colab notebook available in the EGR 103 Google Drive folder
- Logic
- <= < == >= > != work with many types; just be careful about interpreting
not
can reverse whileand
andor
can combine logical expressions; most expressions can be written in two ways (while/if TRUE or while/if not FALSE)- in can ask if a character / substring is in a string or if an element is in a list or tuple
- Basics of decisions using if...elif...else
- Must have logic after if
- Can have as many elif with logic after
- Can have an else without logic at the end
- Flow is solely dependent on indentation!
- Branches can contain other trees for follow-up questions
- Basics of loops using while
- Must have logic; gets evaluated at start and not again until branch ends
- Useful when you do not know how many times a loop will run (input validation example)
- break in a loop can break out early
- continue in a loop goes back to the top early
- Basics of loops using for
- for VAR in ITERABLE
- VAR will take on each item in ITERABLE one at a time; ITERABLE can be a string, list, tuple, array, or range
- range(N) creates something similar to [0, 1, 2, 3, 4, ..., N-1]
- range(M, N) creates something similar to [M, M+1, M+2, ..., N-1]
- range only creates integers
- VAR will take on each item in ITERABLE one at a time; ITERABLE can be a string, list, tuple, array, or range
- for VAR in ITERABLE
Lecture 7 - 2/3 - Loops and Accounting
- The Price is Right!
- Looked at looping through letters in a phrase
- Logic: ITEM in THING will be true if ITEM is a subunit of THING
- "a" in "subway" would be True
- "way" in "subway" would be True
- "as" in "subway" would be False
- Many ways to keep track of items
- Counter variable
- List with different indices to track different items
- Many ways to evaluate items
- For loop with an if tree
- For loop with another for loop
Lecture 8 - 2/6 - Dictionaries
- Dictionaries are collections of key : value pairs set off with { }; keys can be any immutable type (int, float, string, tuple) and must be unique; values can be any type and do not need to be unique
- Dictionary at tutorialspoint
- Storing values in a dictionary
- Different loops
- zip
- Translation demo with Morse code and NATO phonetic alphabet
- Loading lines of text from a file
- Splitting strings with split