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ljwolf / ortools_toy_optimization_models.ipynb
Created August 13, 2018 18:37 — forked from jGaboardi/ortools_toy_optimization_models.ipynb
7x5 OD facility location models with ortools
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@ljwolf
ljwolf / keybase.md
Created June 20, 2018 22:08
keybase.md

Keybase proof

I hereby claim:

  • I am ljwolf on github.
  • I am ljwolf (https://keybase.io/ljwolf) on keybase.
  • I have a public key ASAOhoYdj2vbKVhOoA8JlTTsGCky2vx9HyPsLcJ66IETcQo

To claim this, I am signing this object:

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@ljwolf
ljwolf / Does Projection Matter for Compactness Scores?.ipynb
Created February 16, 2018 20:37
A quick and dirty exploration of the impact of projection on district compactness scores
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@ljwolf
ljwolf / airbnb.csv
Last active February 16, 2018 14:59
An example illustrating Bayesian Estimation Supersedes the T-Test for Bristol Quantitative Social Science Lab
We can't make this file beautiful and searchable because it's too large.
Unnamed: 0,id,listing_url,scrape_id,last_scraped,name,summary,space,description,experiences_offered,neighborhood_overview,notes,transit,access,interaction,house_rules,thumbnail_url,medium_url,picture_url,xl_picture_url,host_id,host_url,host_name,host_since,host_location,host_about,host_response_time,host_response_rate,host_acceptance_rate,host_is_superhost,host_thumbnail_url,host_picture_url,host_neighbourhood,host_listings_count,host_total_listings_count,host_verifications,host_has_profile_pic,host_identity_verified,street,neighbourhood,neighbourhood_cleansed,neighbourhood_group_cleansed,city,state,zipcode,market,smart_location,country_code,country,latitude,longitude,is_location_exact,property_type,room_type,accommodates,bathrooms,bedrooms,beds,bed_type,amenities,square_feet,price,weekly_price,monthly_price,security_deposit,cleaning_fee,guests_included,extra_people,minimum_nights,maximum_nights,calendar_updated,has_availability,availability_30,availability_60,availability_90,availability_365,calendar_last_sc
@ljwolf
ljwolf / plotweights.py
Created February 16, 2018 14:52
small script to plot the weights from a pysal object using polygons in a geopandas dataframe
import matplotlib.pyplot as plt
import numpy as np
def plot_weights(gdf, W, indexed_on='', ax=None):
if ax is None:
f = plt.figure(figsize=(1.6*8, 8))
ax = plt.gca()
gdf.plot(linewidth=.1, color='white', ax=ax)
for idx, neighbors in W:
if idx in W.islands:
We can't make this file beautiful and searchable because it's too large.
Unnamed: 0,id,listing_url,scrape_id,last_scraped,name,summary,space,description,experiences_offered,neighborhood_overview,notes,transit,access,interaction,house_rules,thumbnail_url,medium_url,picture_url,xl_picture_url,host_id,host_url,host_name,host_since,host_location,host_about,host_response_time,host_response_rate,host_acceptance_rate,host_is_superhost,host_thumbnail_url,host_picture_url,host_neighbourhood,host_listings_count,host_total_listings_count,host_verifications,host_has_profile_pic,host_identity_verified,street,neighbourhood,neighbourhood_cleansed,neighbourhood_group_cleansed,city,state,zipcode,market,smart_location,country_code,country,latitude,longitude,is_location_exact,property_type,room_type,accommodates,bathrooms,bedrooms,beds,bed_type,amenities,square_feet,price,weekly_price,monthly_price,security_deposit,cleaning_fee,guests_included,extra_people,minimum_nights,maximum_nights,calendar_updated,has_availability,availability_30,availability_60,availability_90,availability_365,calendar_last_sc
We can't make this file beautiful and searchable because it's too large.
Unnamed: 0,id,listing_url,scrape_id,last_scraped,name,summary,space,description,experiences_offered,neighborhood_overview,notes,transit,access,interaction,house_rules,thumbnail_url,medium_url,picture_url,xl_picture_url,host_id,host_url,host_name,host_since,host_location,host_about,host_response_time,host_response_rate,host_acceptance_rate,host_is_superhost,host_thumbnail_url,host_picture_url,host_neighbourhood,host_listings_count,host_total_listings_count,host_verifications,host_has_profile_pic,host_identity_verified,street,neighbourhood,neighbourhood_cleansed,neighbourhood_group_cleansed,city,state,zipcode,market,smart_location,country_code,country,latitude,longitude,is_location_exact,property_type,room_type,accommodates,bathrooms,bedrooms,beds,bed_type,amenities,square_feet,price,weekly_price,monthly_price,security_deposit,cleaning_fee,guests_included,extra_people,minimum_nights,maximum_nights,calendar_updated,has_availability,availability_30,availability_60,availability_90,availability_365,calendar_last_sc