svHatch

# Taken from https://gis.stackexchange.com/questions/149959/dissolving-polygons-based-on-attributes-with-python-shapely-fiona

from shapely.geometry import shape, mapping
from shapely.ops import unary_union
import fiona
import itertools
with fiona.open('cb_2013_us_county_20m.shp') as input:
    # preserve the schema of the original shapefile, including the crs
    meta = input.meta
    with fiona.open('dissolve.shp', 'w', **meta) as output:

svHatch

# Show UnionizeMe's latest expenditures with hledger
# https://www.unionizeme.org/donate-now#radical-transparency
# http://hledger.org/download (0.27 or greater suggested)

default: demo

unionizeme.csv:
	curl -s -o unionizeme.csv 'https://docs.google.com/spreadsheets/d/1l1FoWxseOP07fBMauapG3hIX5DNVooGQTpQQC0sBNv4/export?format=csv&id=1l1FoWxseOP07fBMauapG3hIX5DNVooGQTpQQC0sBNv4&gid=0'

unionizeme.csv.rules:

svHatch

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!

svHatch

import ipdb
import numpy as np
import numpy.linalg as nl
import matplotlib.pyplot as plt
from scipy.spatial.distance import pdist, cdist, squareform

def makeT(cp):
    # cp: [K x 2] control points
    # T: [(K+3) x (K+3)]
    K = cp.shape[0]

svHatch

from multiprocessing import Pool
import sys
import fiona
from fiona.transform import transform_geom
from shapely.geometry import mapping, shape
import json

def reproject(f, srs_crs, dest_crs):
    f['geometry'] = transform_geom(srs_crs, dest_crs, f['geometry'],
                          antimeridian_cutting=True,

svHatch

from geojson import utils, Feature, FeatureCollection
import random
import json

group = []
for i in range(0, 1000):
	feature = utils.generate_random(featureType='Point', numberFeatures=1, boundingBox=[144,-37,146,-38.5])
	cartons = random.randrange(0, 3000)
	rev = random.randrange(0, 30000)
	newFeat = Feature(geometry=feature, properties={"cartons": cartons, "revenue": rev})