wrobstory

A Leaflet.js map created with Folium and a custom D3 threshold scale, with data bound between the Pandas DataFrame and the TopoJSON. See the Gist for the python code to generate the dataframe. The map was generated with the following Python code:

map_3 = folium.Map(location=[40, -99], zoom_start=4)
map_3.geo_json(geo_path=county_geo, data_out='data3.json', data=df,
               columns=['GEO_ID', 'Median_Household_Income_2011'],
               key_on='feature.id',
               fill_color='PuRd', line_opacity=0.3,
               legend_name='Median Household Income 2011 ($)',
 topojson='objects.us_counties_20m')

wrobstory

A Leaflet.js map created with Folium. This map was generated with the following Python code:

import folium

map_1 = folium.Map(location=[45.372, -121.6972], zoom_start=12,
                   tiles='Stamen Terrain')
map_1.simple_marker([45.3288, -121.6625], popup='Mt. Hood Meadows')
map_1.simple_marker([45.3311, -121.7113], popup='Timberline Lodge')
map_1.create_map(path='mthood.html')

wrobstory

;; Gaussian sum!
user=> (crit/with-progress-reporting (crit/quick-bench (/ (* (+ 1 99999) 99999) 2)))
Warming up for JIT optimisations 5000000000 ...
  compilation occured before 333366 iterations
Estimating execution count ...
Sampling ...
Final GC...
Checking GC...
WARNING: Final GC required 8.548926352381509 % of runtime
Finding outliers ...

wrobstory

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]

# C extensions
*.so

# Distribution / packaging
.Python
env/

wrobstory

A Leaflet.js map created with Folium and the default D3 threshold scale. See the Gist for the python code to generate the dataframe. The map was generated with the following Python code:

map = folium.Map(location=[48, -102], zoom_start=3)
map.geo_json(geo_path=state_geo, data=state_data,
             columns=['State', 'Unemployment'],
             key_on='feature.id',
             fill_color='YlGn', fill_opacity=0.7, line_opacity=0.2,
             legend_name='Unemployment Rate (%)')
map.create_map(path='us_states.html')

wrobstory

A choropleth map created with Folium and Pandas. Pull data into a dataframe, bind to a feature of the GeoJSON, map it. Folium allows you to specify any of the color brewer sequential color groups, and also allows you to specify the d3 quantize scale range:

import folium
import json
import pandas as pd
import vincent

county_data = r'us_county_data.csv'
county_geo = r'us-counties.json'

wrobstory

A Leaflet.js map created with Folium- click on the marker to see the popup text. This map was generated with the following Python code:

map_2 = folium.Map(location=[45.5236, -122.6750], tiles='Stamen Toner',
                   zoom_start=13)
map_2.simple_marker(location=[45.5244, -122.6699], popup='The Waterfront')
map_2.circle_marker(location=[45.5215, -122.6261], radius=500,
                    popup='Laurelhurst Park', line_color='#3186cc',
                    fill_color='#3186cc')
map_2.create_map(path='portland.html')

wrobstory

import pytest

def setup_function(function):
    foo = 1
    function(foo)

def test_thing(thing):
    two = thing + 1
    assert two == 2

wrobstory

wrobstory

In [1]: %paste
from sklearn.datasets import load_iris
from sklearn import tree
import coremltools

iris = load_iris()
clf = tree.DecisionTreeClassifier()
clf = clf.fit(iris.data, iris.target)

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