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View Code? Open in Web Editor NEWThis repository is a Data Science curriculum for history.
This repository is a Data Science curriculum for history.
Week 1 and Week 2 Presentation
Week 2 HW
Q5 and Q6
Q8
Q10
Reaching out to people to provide feedback for Week 2 - 5 Outlines:
A little explanation of the module. DigitalHistory focuses on teaching students, the basic fundamentals of applied Data Science. Our curriculum is designed into two sections, labs and tutorials. Tutorials focus on teaching a specific topic. eg. Python, NumPy, Matplotlib, etc. Labs focus on a comprehension step by step breakdown using all the material taught in a project-based form.
Presentation
(We're going to explore how to split this section into two parts soon.)
Mistake: “Try to keep names relevant, for example len() is a good name for a length() function.” - replace comma with an em dash and add comma after example
Location: Functions: Def Statements
Mistake: “Now here is the important step, you must indent” - replace comma with colon or period
Location: Functions: Def statements
Mistake: “Next you'll see the docstring, this is where you…” - replace comma with colon or period
Location: Functions: Def statements
Mistake: “As soon as we determine that a number is not prime we break out of the for loop.” - add comma after “prime”
Location: Using return example 3
Mistake: “We can actually improve this function by only checking to the square root of the target number, and by disregarding all even numbers after checking for 2.” - remove comma and “by”
Location: Using return example 3
Mistake: “Then, some of us might be curious:” - a little awkward; maybe replace “then” with “now” or remove it
Location: Now Try This 7.0
Mistake: “Briefly describe what you have found here.” - there’s nowhere to do this (assuming it’s meant for students to type somewhere)
Location: Now Try This 7.0
Mistake: “What we will be using in the tutorial is the US Census Demographic Data.” - “We will be using the US Census Demographic Data in this tutorial” might flow better
Location: Practical exercise: about the data set
Mistake: “The data here were collected” - replace “were” with “was” since data is plural, or replace “data” with “datum” if the intention was for it to be singular
Location: Practical exercise: about the data set
Mistake: “As this dataset has so many columns…” - replace “as” with “because”
Location: Practical exercises: select subsets with data
Mistake: “We can treat them very similarly with the major distinction being that tuples are immutable.” - awkward phrasing; maybe replace with “We can treat them very similarly, but keep in mind the major distinction that Tuples are immutable.”
Location: Tuples
Mistake: “Mappings are a collection of objects that are stored by a key, unlike a sequence that stored objects by their relative position.” - this is confusing; maybe replace with “Unlike a sequence that can store objects by their relative position, mappings are a collection of objects that are stored by a key.”
Location: Dictionaries
Mistake: “A quick note, Python has” - replace comma with colon
Location: Dictionaries: constructing a dictionary
Mistake: “For instance if we started off” - add comma after “instance”
Location: Dictionaries: constructing a dictionary
Mistake: “Since checking the length of a sequence is a common task you would want to…” - add comma after task
Location: Functions: Introduction to Functions
Hey y'all. I found this really confusing
https://github.com/bitprj/DigitalHistory/tree/master/Week2-Introduction-to-Python-_-NumPy
Mistake: “discussion and research on about related topics” - I think this is unintentionally repetitive
Location: About this course
Mistake: “Additionally, you will also have access to homeworks for the 7 Tutorials, these homeworks will be similar to the 'Now Try This' sections.” - punctuation error
Location: “Homeworks”
Mistake: Maybe use a different term for “practicum” or define it
Location: Practicums
Mistake: “The reason a field such as data analysis is very important is because, in many cases” - punctuation
Location: What is Data Science and Analytics?
Mistake: “cholera was transmitted by “an agent in the water” than by the accepted theory” - add “rather”
Location: What is Data Science and Analytics?
Mistake: “we can do a lot more with Python” - capitalization
Location: Variable Assignments
Mistake: “wrapped it up with learning” - replace “with” with “by”
Location: Variable Assignments
Mistake: “Python comes with booleans” - clarify phrase “comes with”
Location: Booleans
Mistake: “That's all to booleans!” - replace “to” with “for”
Location: Booleans
Mistake: “Earlier when discussing strings we introduced the concept of a sequence” - add comma after “strings”
Location: Lists
Mistake: “Lists in Python however,” - add comma after “Python”
Location: Lists: Basic List Methods
Mistake: “By default pop takes off the last index” - add comma after “default”
Location: Lists: Basic List Methods
Mistake: “but now there are two levels for the index. The items in the matrix object, and then the items inside that list!” - replace period with a colon, remove comma, remove “then”
Location: Lists: Nesting Lists
Mistake: “In Python tuples are very similar to lists, however, unlike lists they are immutable meaning they can not be changed” - “In Python, tuples are very similar to lists. However, unlike lists, they are immutable— meaning they cannot be changed.” might be easier to digest
Location: Tuples
Mistake: “You'll have an intuition of how to use tuples” - awkward phrasing
Location: Tuples
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