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from category_encoders.binary import BinaryEncoder
from category_encoders.basen import BaseNEncoder
from sklearn.compose import ColumnTransformer
import pandas as pd
import pickle
with open("osource.pkl", "rb") as f:
osource = pickle.load(f)
be = BinaryEncoder(handle_missing="return_nan")
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datarian / US Zip Code Geolocations from 2018 Government Data
Created March 17, 2019 13:40 — forked from abatko/US Zip Code Geolocations from 2018 Government Data
All US zip codes with their corresponding geolocations (latitude and longitude coordinates). Comma delimited for your database goodness. Source: http://www.census.gov/geo/maps-data/data/gazetteer.html > 2018 Census U.S. Gazetteer files > ZIP Code Tabulation Areas
ZIP,LAT,LNG
00601,18.180555, -66.749961
00602,18.361945, -67.175597
00603,18.455183, -67.119887
00606,18.158327, -66.932928
00610,18.295366, -67.125135
00612,18.402253, -66.711397
00616,18.420412, -66.671979
00617,18.447538, -66.557681
00622,17.991245, -67.153993
@datarian
datarian / US Zip Codes from 2013 Government Data
Created March 17, 2019 08:30 — forked from erichurst/US Zip Codes from 2013 Government Data
All US zip codes with their corresponding latitude and longitude coordinates. Comma delimited for your database goodness. Source: http://www.census.gov/geo/maps-data/data/gazetteer.html
This file has been truncated, but you can view the full file.
ZIP,LAT,LNG
00601,18.180555, -66.749961
00602,18.361945, -67.175597
00603,18.455183, -67.119887
00606,18.158345, -66.932911
00610,18.295366, -67.125135
00612,18.402253, -66.711397
00616,18.420412, -66.671979
00617,18.445147, -66.559696