Data directory for my bl.ocks.
- us.json - US states, counties and land boundaries
osm-building-import┋ master⚡ ᴥ osmosis --read-xml osm/features.osm --truncate-pgsql database=osm_test port=15432 --wp database=osm_test port=15432 | |
Oct 10, 2014 11:56:59 AM org.openstreetmap.osmosis.core.Osmosis run | |
INFO: Osmosis Version 0.42-6-gf39a160-dirty | |
Oct 10, 2014 11:56:59 AM org.openstreetmap.osmosis.core.Osmosis run | |
INFO: Preparing pipeline. | |
Oct 10, 2014 11:56:59 AM org.openstreetmap.osmosis.core.Osmosis main | |
SEVERE: Execution aborted. | |
org.openstreetmap.osmosis.core.OsmosisRuntimeException: Argument port for task 2-truncate-pgsql was not recognised. | |
at org.openstreetmap.osmosis.core.pipeline.common.TaskManagerFactory.createTaskManager(TaskManagerFactory.java:64) | |
at org.openstreetmap.osmosis.core.pipeline.common.Pipeline.buildTasks(Pipeline.java:50) |
<!doctype html> | |
<meta charset="utf-8"> | |
<body> | |
<style media="screen"> | |
body { | |
margin: 0; | |
} | |
.supermarket { | |
fill: red; |
function long2tile(lon,zoom) { | |
return (Math.floor((lon+180)/360*Math.pow(2,zoom))); | |
} | |
function lat2tile(lat,zoom) { | |
return (Math.floor((1-Math.log(Math.tan(lat*Math.PI/180) + 1/Math.cos(lat*Math.PI/180))/Math.PI)/2 *Math.pow(2,zoom))); | |
} | |
function tile2long(x,z) { | |
return (x/Math.pow(2,z)*360-180); |
drop table if exists target_homes; | |
with | |
supermarket_zones as (select st_expand(geom, 0.0045) as zone, 5 as score from osm_polygons where osm_polygons.shop='supermarket'), | |
rail_stop_zones as (select st_expand(geom, 0.0045) as zone, 5 as score from trimet_rail_stops), | |
park_zones as (select st_expand(geom, 0.0045) as zone, 2 as score from osm_polygons where osm_polygons.leisure='park'), | |
target_buildings as ( | |
select * from supermarket_zones inner join buildings on st_intersects(supermarket_zones.zone, buildings.geom) where buildings.subarea='City of Portland' | |
union select * from rail_stop_zones inner join buildings on st_intersects(rail_stop_zones.zone, buildings.geom) where buildings.subarea='City of Portland' | |
) |
<!doctype html> | |
<meta charset="UTF-8"> | |
<style type="text/css" media="screen"> | |
.path { | |
stroke: #c00; | |
stroke-width: 1; | |
fill: none; | |
} | |
</style> | |
<script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script> |
.DS_Store | |
node_modules | |
us-judicial-districts.zip | |
build |
Data directory for my bl.ocks.
Hi,
I'm looking through the City Council agenda items and noticed there is a great deal of information in each one. However, all of the documents are in the proprietary PDF format which makes them hard for machines (computers) to parse. If I were looking to extract some meaningful data (say expense, revenue, and affected city areas), I would need to comb through each one of these files manually.
It would be great if the city were to release these documents as HTML or XML documents. Even plain text is better than PDF for parsing!
With the above in mind, I have two questions:
import pandas as pd | |
import numpy as np | |
import matplotlib | |
import matplotlib.pyplot as plt | |
import glob | |
import os.path | |
font = {'family' : 'sans-serif', | |
'size' : 8} |