Editing Community Data Science Course (Spring 2023)/Week 3 lecture notes

== Online Data Sets: An Important Question ==

Can you get bulk access to data?

'''Bad Signs:'''

* You must authenticate as a particular user in order to access data, and you can only see data for that user. (For example: you must log into Instagram's API as a particular user as per [https://www.instagram.com/developer/endpoints/users/ this link!])

'''Good signs:'''

* The organization owning the data wants everyone to access it. Like wikipedia or most government data.
* You may have to authenticate as a particular user, but you can access general data.
* For example: once you log into Reddit, you can get all posts about almost anything ([https://developer.twitter.com/en/docs/geo/place-information/api-reference/get-geo-id-place_id Twitter API Docs])

==Programming lecture outline==

* Dictionaries!
** Purpose (use dictionaries to store key/value pairs)
** Initialization <code>{}</code>
** Accessing elements
** Adding elements
** Changing elements
** <code>.values()</code> and <code>.values()</code>
** using <code>in</code> to look into dictionaries
** using <code>for</code> loops to iterate over dictionaries (e.g., lets build a list of every letter in the alphabet using wordplay data)
** A few notes about dictionaries:
*** A given key can only have one value, but multiple keys can have the same value.
*** Dictionaries do not guarantee ordering (although if you are using new versions of Python, order will be preserved).
* Additional loop control
** <code>break</code>
** <code>continue</code>
** ''Note:'' These can be useful in combination to if statements and can also be super useful for debugging!
* Writing to files:
** Using the <code>open("whatever.tsv", "w")</code> function
** Using the <code>with open() as my_file:</code> statement
** Writing to a file with <code>print(file=my_file)</code>
** Writing a tab-separated value file using "\t" (make sure we leave a header!)
** Now lets open it up and make a little graph
* Defining our own functions!
* A little bit on looking for help (if it hasn't come up already)
** Looking at StackOverflow
** Walking through the Python API documentation
** Using a reference card or cheatsheet

====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 "<stdin>", line 1, in <module>
 KeyError: 'Eve'
 >>> "Eve" in your_dict
 False
 >>> "Alice" in your_dict
 True
 >>> your_dict.get("Eve")
 >>> person = your_dict.get("Eve")
 >>> print(person)
 None
 >>> print(type(person))
 <type 'NoneType'>
 >>> your_dict.get("Alice")
 'chocolate'

====Changing elements of a dictionary====

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

====Histograms====

'''Challenge''': using wordplay example from last week, count the number of words that start with each letter. 

This kind of problem is very common Data Science, and it is easy with a dictionary.

(note: I will post the solution after class)

====For-loops and dictionaries====

There are two common ways to iterate through dictionaries:

 >>> ages = {'Tommy': 34, Heather: 30, 'Joanna': 20}
 >>> for key in ages:
 >>>     print(key + " is " + str(ages[key]) + " years old")

 >>> for key, value in ages.items():
 >>>     print(key + " is " + str(value) + " years old")