Editing Community Data Science Workshops (Core)/Day 3 Lecture
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Welcome to the Saturday lecture section of the Community Data Science Workshop Session 3! For about 140 minutes, we'll work through an example of a Python program end-to-end that answers of simple questions using data from the Wikipedia API via both a lecture and hand-on exercises. | Welcome to the Saturday lecture section of the Community Data Science Workshop Session 3! For about 140 minutes, we'll work through an example of a Python program end-to-end that answers of simple questions using data from the Wikipedia API via both a lecture and hand-on exercises. | ||
== Resources == | |||
* [https://communitydata. | * [https://communitydata.cc/~mako/cdsw-sp2016-lecture3-20160507.ogv Screencast/recording of the lecture] (934MB) — The file should be viewable in Firefox and many other browsers. If you have trouble playing it, you can download [https://www.videolan.org/vlc/index.html the VLC media player] which will be a able to play it on Windows, OSX, or GNU/Linux. | ||
== Material for the lecture == | == Material for the lecture == | ||
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For the lecture, you will need two files. Download both of these to your computer by using right or control click on the link and then using ''Save as'' or ''Save link as''. Keep track of where you put the files. | For the lecture, you will need two files. Download both of these to your computer by using right or control click on the link and then using ''Save as'' or ''Save link as''. Keep track of where you put the files. | ||
* | * http://mako.cc/teaching/2015/cdsw-autumn/harrypotter-wikipedia-cdsw.zip | ||
* http://communitydata. | * http://communitydata.cc/~mako/hp_wiki.tsv | ||
== Overview of the day == | == Overview of the day == | ||
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** We'll focus on manipulating data in Python | ** We'll focus on manipulating data in Python | ||
** Visualizing things in Google Docs | ** Visualizing things in Google Docs | ||
* Lunch ( | * Lunch (vegetarian Greek!) | ||
* Project based work | * Project based work | ||
** Wikipedia | |||
** Twitter | |||
** Data.seattle.gov | ** Data.seattle.gov | ||
** [[Matplotlib]] | |||
** Your own projects! | ** Your own projects! | ||
* Wrap-up! | * Wrap-up! | ||
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** defining your own functions with <code>def foo(argument):</code> and <code>return bar</code> | ** defining your own functions with <code>def foo(argument):</code> and <code>return bar</code> | ||
** The <code>.update()</code> function that is associated with dictionaries. | ** The <code>.update()</code> function that is associated with dictionaries. | ||
'''Step 2: Walking through a Program''' | '''Step 2: Walking through a Program''' | ||
* Walk-through of <code> | * Walk-through of <code>get_hpwp_dataset.py</code> | ||
* Look at dataset with | * Look at dataset with <code>more</code> and/or in spreadsheet | ||
'''Step 3: Loading Data Back In''' | '''Step 3: Loading Data Back In''' | ||
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*** we can also open them for reading with <code>open('file', 'r', encoding="utf-8")</code> | *** we can also open them for reading with <code>open('file', 'r', encoding="utf-8")</code> | ||
** csv.DictReader() | ** csv.DictReader() | ||
* Basic counting: <code> | * Basic counting: <code>hpwp-minor.py</code> | ||
** Answer question: ''What proportion of edits to Wikipedia Harry Potter articles are minor?'' | ** Answer question: ''What proportion of edits to Wikipedia Harry Potter articles are minor?'' | ||
*** Count the number of minor edits and calculate proportion | *** Count the number of minor edits and calculate proportion | ||
* Looking at time series data <code> | * Looking at time series data <code>hpwp-trend.py</code> | ||
** "Bin" data by day to generate the trend line | ** "Bin" data by day to generate the trend line | ||
* Exporting and visualizing data | * Exporting and visualizing data | ||
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** Export dataset on articles over users | ** Export dataset on articles over users | ||
** Load data into Google Docs | ** Load data into Google Docs | ||
[[Category:Shared_Content]] | [[Category:Shared_Content]] |