calvinmetcalf

Basic example of taking an output from our server and putting it on a map. As leaflet allows you to add geoJSON directly, we convert it from esri's JSON format to a more standard one.

erussell

/data
/mosaic.gdb
/scratch.gdb

odoe

# This is a script that I use to convert geojson to
# features in a file gdb
# Step 1. Use the REST page of an ArcGIS Map Service to
# 	get the esri json results of the data you want.
# Step 2. I used my EsriJSON to GeoJSON app to convert
#	the results to geojson. http://esritogeo.herokuapp.com/
# Step 3. In ArcMap, use the python window to create a
#	python dictionary of your geojson.
# Step4. Use the following script to convert that geojson
#	into featureclasses and then merge them.

seberg

def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toend=True):
    """Create a view of `array` which for every point gives the n-dimensional
    neighbourhood of size window. New dimensions are added at the end of
    `array` or after the corresponding original dimension.
    
    Parameters
    ----------
    array : array_like
        Array to which the rolling window is applied.
    window : int or tuple

iamatypeofwalrus

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time

frankrowe

 import shapefile
   # read the shapefile
   reader = shapefile.Reader("my.shp")
   fields = reader.fields[1:]
   field_names = [field[0] for field in fields]
   buffer = []
   for sr in reader.shapeRecords():
       atr = dict(zip(field_names, sr.record))
       geom = sr.shape.__geo_interface__
       buffer.append(dict(type="Feature", \

nsonnadsnip

function mouseOn () {
    var circleUnderMouse = this;
    d3.selectAll('.rectGroup').transition().style('opacity',function () {
        return (this === circleUnderMouse) ? 1.0 : 0.5;
    });
}

RobertSudwarts

def degrees_to_cardinal(d):
    '''
    note: this is highly approximate...
    '''
    dirs = ["N", "NNE", "NE", "ENE", "E", "ESE", "SE", "SSE",
            "S", "SSW", "SW", "WSW", "W", "WNW", "NW", "NNW"]
    ix = int((d + 11.25)/22.5)
    return dirs[ix % 16]

Keareys

Primary Census API Documentation Page:
http://www.census.gov/data/developers/data-sets.html

ACS Summary File Documentation

Other Useful Documentation Examples:
http://www.opengeocode.org/tutorials/USCensusAPI.php
https://www.socialexplorer.com/data/ACS2010/documentation/781dcba1-deed-47f9-a223-0cbc4e2b65b6

NicolleLouis

#!/usr/bin/python3.5
# -*-coding:Utf-8 -*

import random
import operator
import time
import matplotlib.pyplot as plt

temps1 = time.time()