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""" | |
Reduce the size of the store fixture by removing adminareas | |
""" | |
from django.config.serializers import yaml | |
store = yaml.load(open("store.yaml")) | |
small_store = [itm for itm in store | |
if not itm['model'] == 'l10n.adminarea' or | |
(itm['model'] == 'l10n.adminarea' and itm['fields']['country'] == 231)] | |
s = yaml.dump(small_store) |
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size(520, 620) | |
from math import pi | |
data = [ | |
#Pattern,expedia.com,hotel-guides.us,travel.yahoo.com,travelocity.com,tripadvisor.com | |
['[x] hotel',0.02154,0.00903,0.35186,0.16603,0.45155], | |
['[x] hotel [x]',0.00000,0.00000,0.14872,0.26750,0.58378], | |
['[x] inn [x]',0.03185,0.00000,0.00000,0.24957,0.71859], | |
['hotel [x]',0.01385,0.02769,0.31154,0.23692,0.41000], | |
['hotel in [x]',0.03216,0.00000,0.53631,0.19191,0.23963], |
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size(520, 620) | |
from math import pi | |
data = [ | |
#Pattern,expedia.com,hotel-guides.us,travel.yahoo.com,travelocity.com,tripadvisor.com | |
['[x] hotel',0.02154,0.00903,0.35186,0.16603,0.45155], | |
['[x] hotel [x]',0.00000,0.00000,0.14872,0.26750,0.58378], | |
['[x] inn [x]',0.03185,0.00000,0.00000,0.24957,0.71859], | |
['hotel [x]',0.01385,0.02769,0.31154,0.23692,0.41000], | |
['hotel in [x]',0.03216,0.00000,0.53631,0.19191,0.23963], |
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size(520, 500) | |
from math import pi | |
data = [ | |
#Pattern,expedia.com,hotel-guides.us,travel.yahoo.com,travelocity.com,tripadvisor.com | |
['[x] hotel',0.02154,0.00903,0.35186,0.16603,0.45155], | |
['[x] hotel [x]',0.00000,0.00000,0.14872,0.26750,0.58378], | |
['[x] inn [x]',0.03185,0.00000,0.00000,0.24957,0.71859], | |
['hotel [x]',0.01385,0.02769,0.31154,0.23692,0.41000], | |
['hotel in [x]',0.03216,0.00000,0.53631,0.19191,0.23963], |
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size(520, 500) | |
from math import pi | |
data = [ | |
#Pattern,expedia.com,hotel-guides.us,travel.yahoo.com,travelocity.com,tripadvisor.com | |
['[x] hotel',0.02154,0.00903,0.35186,0.16603,0.45155], | |
['[x] hotel [x]',0.00000,0.00000,0.14872,0.26750,0.58378], | |
['[x] inn [x]',0.03185,0.00000,0.00000,0.24957,0.71859], | |
['hotel [x]',0.01385,0.02769,0.31154,0.23692,0.41000], | |
['hotel in [x]',0.03216,0.00000,0.53631,0.19191,0.23963], |
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' Add this to the page that contains the master PivotTable | |
' assumes the page containing the slave PivotTables is named "Transform" | |
' | |
' | |
' On PivotTable update in the Display page | |
Private Sub Worksheet_PivotTableUpdate(ByVal Target As PivotTable) | |
Dim masterPf As PivotField | |
Dim slavePf As PivotField | |
Dim pt As PivotTable | |
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" | |
"http://www.w3.org/TR/html4/loose.dtd"> | |
<html lang="en"> | |
<head> | |
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
<title>untitled</title> | |
<!-- an example of how to do two divs side by side --> | |
<style type="text/css" media="screen"> |
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""" | |
Fetch people for Twitalyzer's mechanical turk. Will fetch and submit | |
Twitalyzer turk people forever with DELAY seconds between each pull. | |
Hit Ctrl-C (OSX, Linux) or Ctrl-D (Windows) to stop. | |
To use, just run: | |
> python twitalizer_turk.py |
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size(520, 620) | |
from math import pi | |
data = [ | |
#Pattern,expedia.com,hotel-guides.us,travel.yahoo.com,travelocity.com,tripadvisor.com | |
['[x] hotel',0.02154,0.00903,0.35186,0.16603,0.45155], | |
['[x] hotel [x]',0.00000,0.00000,0.14872,0.26750,0.58378], | |
['[x] inn [x]',0.03185,0.00000,0.00000,0.24957,0.71859], | |
['hotel [x]',0.01385,0.02769,0.31154,0.23692,0.41000], | |
['hotel in [x]',0.03216,0.00000,0.53631,0.19191,0.23963], |
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" | |
"http://www.w3.org/TR/html4/loose.dtd"> | |
<html lang="en"> | |
<head> | |
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
<title>Simple Raphael Maps Using D3 Projections</title> | |
<script type="text/javascript" charset="utf-8" src="raphael-min.js"></script> | |
<script type="text/javascript" charset="utf-8" src="geo-projection.js"></script> | |
<script type="text/javascript" charset="utf-8" src="us.svg.js"></script> |