Community Data Science Workshops (Fall 2015)/Day 3 Projects: Difference between revisions

Revision as of 01:58, 2 November 2015

In the afternoon sessions, there will once again be three options:

Option 1: Harry Potter on Wikipedia — This talk will continue directly from lecture and we will use the same dataset of the metadata from all the Wikipedia articles about Harry Potter.
Option 2: TWITTER INFO AND LINK GOES HERE
Option 3: Civic data — If you want to visualize some Seattle construction data, this is the room for you. We will go over how to pull timeseries and location data from APIs, and visualize it using Google Apps.
Option 4: Independent study. If you have an idea for a project to build or analyze a dataset and you think you can work 70-80% independently on it, this is also the room for you! Mentors will be around to help you as you get stuck and to give you advice! So if are looking for more detailed help with, say, the Twitter API, then this is the room for you.

@@ Line 2: / Line 2: @@
 * '''Option 1:''' [[Harry Potter on Wikipedia]] — This talk will continue directly from lecture and we will use the same dataset of the metadata from all the Wikipedia articles about Harry Potter.
-* '''Option 2:''' [[Community_Data_Science_Workshops_(Fall_2014)/Day_3_projects/Matplotlib_Session|Data visualization with Matplotlib]] — In this session we will focus on making beautiful and nuanced plots using a powerful graphing library within Python. We'll be using the dataset created this morning with wikipedia edit information, and data sets from other web APIs.
+* '''Option 2:''' TWITTER INFO AND LINK GOES HERE
-* '''Option 3:''' '''[[Community_Data_Science_Workshops_(Spring_2015)/Day_3_Projects/Civic_data|Civic data]] & self-directed project room''' — If you want to [[Community_Data_Science_Workshops_(Spring_2015)/Day_3_Projects/Civic_data|visualize some Seattle construction data]], this is the room for you. We will go over how to pull timeseries and location data from APIs, and visualize it using Google Apps. If you have an idea for a project to build or analyze a dataset and you think you can work 70-80% independently on it, this is ''also'' the room for you! Mentors will be around to help you as you get stuck and to give you advice! So if are looking for more detailed help with, say, the Twitter API, then this is the room for you.
+* '''Option 3:''' '''[[Community_Data_Science_Workshops_(Fall_2015)/Day_3_Projects/Civic_data|Civic data]]''' — If you want to visualize some Seattle construction data, this is the room for you. We will go over how to pull timeseries and location data from APIs, and visualize it using Google Apps.
+* '''Option 4:''' Independent study.  If you have an idea for a project to build or analyze a dataset and you think you can work 70-80% independently on it, this is ''also'' the room for you! Mentors will be around to help you as you get stuck and to give you advice! So if are looking for more detailed help with, say, the Twitter API, then this is the room for you.
+<!-- [[Community_Data_Science_Workshops_(Fall_2014)/Day_3_projects/Matplotlib_Session|Data visualization with Matplotlib]] — In this session we will focus on making beautiful and nuanced plots using a powerful graphing library within Python. We'll be using the dataset created this morning with wikipedia edit information, and data sets from other web APIs. -->
 [[Category:Fall_2015_series]]