lukewhyte

node buildLegend.js -w ${WIDTH} -h ${HEIGHT} # Build and output legend.svg, minus first line so it can be merged with topo.svg

tail -n +1 < legend.svg >> topo.svg

# clean up dir
find . -name "*.zip" -exec rm -f {} \;
rm states.geojson metroareas.geojson circles.geojson topo.geojson legend.svg

lukewhyte

#! /usr/bin/env node
const fs        = require('fs');
const D3Node    = require('d3-node');
const parseCSV  = require('csv-parse/lib/sync');

// Create a new D3Node instance and then save the path to the d3 library for standalone use.
const d3n   = new D3Node();
const d3    = d3n.d3;

// Load in our CSV file, we'll use this to set our radius domain again.

lukewhyte

geoproject "${PROJECTION}.fitSize([${WIDTH}, ${HEIGHT}], d)" < topo.geojson | # Scale the geojson to needed specs

ndjson-split 'd.features' | # convert to ndjson

geo2svg --newline-delimited -w ${WIDTH} -h ${HEIGHT} | # convert ndjson to svg

sed '$d' > topo.svg # remove last line for splice with legend and output

lukewhyte

#! /usr/bin/env node
const fs = require('fs');

// Import the state geodata and the metro area circles geodata
const states    = JSON.parse(fs.readFileSync('./states.geojson', 'utf8'));
const circles   = JSON.parse(fs.readFileSync('./circles.geojson', 'utf8'));

// Filter and map the state features to include as little data as possible
const parseStates = features => features.map(({ type, properties, geometry }) => ({
    type,

lukewhyte

#! /usr/bin/env node
const fs        = require('fs');
const turf      = require('@turf/turf');
const parseCSV  = require('csv-parse/lib/sync');
const d3        = require('d3');

// Import the metro areas geodata as an object and the percent of undocumented residents data as an array of obj.
const metro         = JSON.parse(fs.readFileSync('./metroareas.geojson', 'utf8'));
const undocumented  = parseCSV(fs.readFileSync('./metro-area-percent-undocumented.csv', 'utf8'), { columns: true });

lukewhyte

shp2json cb_2017_us_state_20m.shp > states.geojson # Convert state shapefile to geojson

shp2json cb_${YEAR}_us_cbsa_20m.shp > metroareas.geojson # Convert metro area shapefile to geojson

lukewhyte

#!/bin/bash

# Year to pull census geo data from
YEAR=2017

# Conditionally download the Pew data
if [ ! -f metro-area-percent-undocumented.csv ]; then
    curl -Lo metro-area-percent-undocumented.csv \
      "https://query.data.world/s/awyahzfiikyoqi5ygpvauqslwmqltr"
fi

lukewhyte

// Includes functions for exporting active sheet or all sheets as JSON object (also Python object syntax compatible).
// Tweak the makePrettyJSON_ function to customize what kind of JSON to export.

var FORMAT_ONELINE   = 'One-line';
var FORMAT_MULTILINE = 'Multi-line';
var FORMAT_PRETTY    = 'Pretty';

var LANGUAGE_JS      = 'JavaScript';
var LANGUAGE_PYTHON  = 'Python';

lukewhyte

^(?!Warning:).*$

lukewhyte

/**
  * used to populate the source List... (so we can add sources to reports)
  */
$scope.filterSources = {
  filterVal: '',

  privatePublic: 'all',

  resetPagination: false,