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==Getting started== * open "notube_logs/analytics.html#2012-02-04" in a modern browser from the desktop e.g. file:///Users/libby/notube_logs/analytics.html#2012-02-04 * you should see some pretty graphs showing what we've been doing on irc lately ==Background== It's designed to show you some basic graphs and data summarising some sort of activity. It was designed to be used with social networking activity but here we've applied it to some other ideas. The design is by http://fabrique.nl from a brief by [email protected] Because it has applications with various datasets I've created several abstractions over the graphs. The raw data (from logs, or hansard or wherever) is processed in a separate customised javascript file. The result of that is passed to the html file 'analytics.html' which is basically reuseable for lots of different situations. Some of these abstractions are less abstract than others. I had trouble characteristing piecharts and the top two and top five types. ==Types of analytic== * number -> a number * text -> a piece of text * text_list -> several words * actvities_list -> titles and links attached to datetime * actvities_grouped -> titles and links grouped by datetime * hourly_count -> number of something per hour * pie -> pie chart * top_two -> line graph for most frequent items now, plotted over last 5 months * top_five -> horizontal stacked bar chart for most frequent items now and a month ago Examples: * number result.push({"text":"Televison minutes in the last two weeks", "type":"numeric", "value": 24}); * text result.push({"text":"Is your favourite genre (in 10% of all programmes you watched)", "type":"single_text", "value": "Soaps"}); * text_list result.push({"text":"Things you talked about","type":"text_list","value":["Pater Gabriel", "RAI Team", "Franz Ferdinand"]}) * activities_list result.push({"text":"What you've watched or listened to recently","type":"activities_list", "value":{ "link": "http://www.bbc.co.uk/programmes/b007jnd9", "texttime": "Friday, 27 January 2012", "time": Fri Jan 27 2012 15:58:27 GMT+0000 (GMT), "title": "Charles Dickens - Barnaby Rudge" },{},{}]... }); * actvities_grouped result.push({"text":"What you've watched or listened to recently","type":"activities_grouped", "value":{Fri Jan 27 2012 00:00:00 GMT+0000 (GMT): [ "link": "http://www.bbc.co.uk/programmes/b007jnd9", "texttime": "Friday, 27 January 2012", "time": Fri Jan 27 2012 15:58:27 GMT+0000 (GMT), "title": "Charles Dickens - Barnaby Rudge" ], []... }}); * hourly_count (array index represents the hour) result.push({"text":"When you watch and listen","type":"hourly_count","value": [5: 1,6: 1, 7: 2, 8: 2, 9: 3,10: 1,12: 2,13: 5,14: 2,15: 1] }); * pie result.push({"text":"Favourite Programmes","type":"pie","value":{ "Ambridge Extra": 44,"Ballylenon": 28,"Book of the Week": 26, } }); * top_two (optimised for the graph display, so perhaps a bit confusing) result.push({"text":""Top 2 interests this month","type":"top_two","value":[[],[],[],[]]}); * four arrays, the first two are the data for the two interests, third is a list of the names for the data, and fourth is a list of the month names for the data arrays: 0: y (maps to name) 1: x (maps to month name) * top_five (optimised for the graph display, so perhaps a bit confusing) The idea is to comare the frequency of an item over 5 months result.push({"text":""Top 5 interests this month","type":"top_five","value":[[],[],[]]}); * three arrays - the first two represent the data, respectively the current month and the last month, the third is list of names of the items. * the data arrays are themsleves arays of 3 items each: 0: the y coordinate (mapped to names array) 1: the x-starting coordinate y: the x-ending coordinate
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