Difference between revisions of "EGR 103/Concept List Spring 2020"
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(Created page with "== Lecture 1 - Introduction == * Class web page: [http://classes.pratt.duke.edu/EGR103S20/ EGR 103L]; assignments, contact info, readings, etc - see slides on Errata/Notes pag...") |
(→Lecture 3 - "Number" Types) |
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** Focus later: dictionary, set | ** Focus later: dictionary, set | ||
* int: integers; Python can store these perfectly | * int: integers; Python can store these perfectly | ||
− | * float: floating point numbers - "numbers with decimal points" - Python sometimes has problems | + | * float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly |
* array | * array | ||
** Requires numpy, usually with <code>import numpy as np</code> | ** Requires numpy, usually with <code>import numpy as np</code> |
Revision as of 20:05, 13 January 2020
Contents
Lecture 1 - Introduction
- Class web page: EGR 103L; assignments, contact info, readings, etc - see slides on Errata/Notes page
- Sakai page: Sakai 103L page; grades, surveys and tests, some assignment submissions
- CampusWire page: CampusWire 103L page; message board for questions - you need to be in the class and have the access code 6393 to subscribe.
Lecture 2 - Programs and Programming
- Seven steps of programming -
- Watch video on Developing an Algorithm
- Watch video on A Seven Step Approach to Solving Programming Problems
Lecture 3 - "Number" Types
- To play with Python:
- Install it on your machine or a public machine: Download
- Quick tour of Python
- Editing window, variable explorer, and console
- Run icon (F5)
- You are not expected to remember any of the specifics about how Python stores things or works with them yet!
- Python is a "typed" language - variables have types
- We will use eight types:
- Focus of the day: int, float, and array
- Basics today, focus a little later: string, list, tuple
- Focus later: dictionary, set
- int: integers; Python can store these perfectly
- float: floating point numbers - "numbers with decimal points" - Python sometimes has problems storing floating point items exactly
- array
- Requires numpy, usually with
import numpy as np
- Organizational unit for storing rectangular arrays of numbers
- Requires numpy, usually with
- Math with "Number" types works the way you expect
- ** * / // % + -
- 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 string contains an immutable collection of characters
- Using + with strings concatenates strings
- Using * with strings makes a string with the original repeated
- A tuple contains an immutable collection of other types
- Using + with tuples concatenates tuples
- Using * with tuples makes a tuple with the original repeated
- A list contains an immutable collection of other types
- Using + with lists concatenates lists
- Using * with lists makes a list with the original repeated
Lecture 4 - More on Types
- Relational operators can compare "Number" Types and work the way you expect with True or False as an answer
- < <= == >= > !=
- 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
- More advanced slices:
- 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 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!