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[
{"words": "the sun did not shine it was too wet to play so we sat in the house all that cold cold wet day"},
{"words": "i sat there with sally we sat there we two and i said how i wish we had something to do"},
{"words": "too wet to go out and too cold to play ball so we sat in the house we did nothing at all"},
{"words": "so all we could do was to sit sit sit sit and we did not like it not one little bit"},
{"words": "and then something went bump how that bump made us jump we looked then we saw him step in on the mat we looked and we saw him the cat in the hat and he said to us why do you sit there like that i know it is wet and the sun is not sunny but we can have lots of good fun that is funny"},
{"words": "i know some good games we could play said the cat i know some new tricks said the cat in the hat a lot of good tricks i will show them to you your mother will not mind at all if i do"},
{"words": "then sally and i did not know what to say our mother was out of the house for the day"},
{"words": "but o
@nbergseng
nbergseng / README.md
Last active August 29, 2015 14:15 — forked from demmer/README.md

Juttle Wordcloud

This gist adapts a wordcloud visualization from http://www.jasondavies.com/wordcloud/ as a Juttle view, adding transitions between batches for updates.

As a silly little showcase, the demonstration program calculates a frequency count of words from Dr Seuss' "The Cat in the Hat" (text pulled from http://paulandlizdavies.com/poems/cat.htm) by splitting the words from each page into separate points, then counting the words by frequency and showing them in the wordcloud and a barchart.

@nbergseng
nbergseng / main.juttle
Created January 7, 2015 18:26
Housing Prices
source "https://github.com/datasets/house-prices-us/blob/master/data/cities-month.csv" | @table
@nbergseng
nbergseng / main.juttle
Created January 7, 2015 18:22
Working Lobbyists
source "https://gist.githubusercontent.com/nbergseng/023dbd6e45645c247e53/raw/9b3acbc98c4fd204aac3a30baee4bc826dc96be4/lobby.csv" | @table
@nbergseng
nbergseng / foodtruck.csv
Created January 7, 2015 18:19
Food Trucks
We can make this file beautiful and searchable if this error is corrected: It looks like row 3 should actually have 23 columns, instead of 17 in line 2.
locationid,Applicant,FacilityType,cnn,LocationDescription,Address,blocklot,block,lot,permit,Status,FoodItems,X,Y,Latitude,Longitude,Schedule,NOISent,Approved,Received,PriorPermit,ExpirationDate,Location
598046,Missing Link SF,,103000,01ST ST: ELIM ALY to MISSION ST (72 - 99),97 01ST ST,3709008,3709,008,14MFF-0133,REQUESTED,smoked sausages: deer: wild boar: pheasant: buffalo: beef: turkey: coleslaw: vegetarian baked beans,6013385.483,2115736.96,37.7901633841957,-122.39754345993,http://bsm.sfdpw.org/PermitsTracker/reports/report.aspx?title=schedule&report=rptSchedule&params=permit=14MFF-0133&ExportPDF=1&Filename=14MFF-0133_schedule.pdf,,,Nov 10 2014 2:57PM,0,,"(37.7901633979667, -122.39754345992)"
526147,Cheese Gone Wild,Truck,106000,01ST ST: NATOMA ST to HOWARD ST (165 - 199),400 HOWARD ST,3720008,3720,008,14MFF-0035,APPROVED,Grilled Cheese Sandwiches,6013858.05956,2115347.09492,37.7891192076677,-122.395881039335,http://bsm.sfdpw.org/PermitsTracker/reports/report.aspx?title=schedule&report=rptSchedule&params=
@nbergseng
nbergseng / README.md
Created January 7, 2015 17:26
Live and Historical Data

Live Data, Meet Historical

Jut lets you analyze live data, historical data or both. This showcase taps into response time data from our synthetic demo generator to combine the last two minutes of history with the live firehose.

Your Turn:

  • Line 2: Change the -from time to :5 minutes ago:
  • Line 4, 6 & 7: Change "service" to "host"
  • Line 3: Change the batch interval to :5 seconds:
@nbergseng
nbergseng / main.juttle
Created January 5, 2015 18:35
Test Gist
emitter | @table
@nbergseng
nbergseng / README.md
Created November 13, 2014 18:23
Bad import format

Stop importing bad data!

This juttle tries to import a file in an unaccepted format.

Blow up your browser based data engine with ease!

This guy generates awesome out of error points, which generate a warning from the DE. These warnings and errors are now i18n-ized thanks to Andrew D. and Henri!