Dataset: Locations Of Home Improvement Stores

About this Dataset

Locations Of Home Improvement Stores

This repository collects a cross-section of data of Lowe's and Home Depot's store locations across the United States. The following data files are included:

CBSA.csv - A list of census based statistical areas with selected characteristics.
census.csv - Selected CDP characteristics
entry.csv - The actual locations for Lowe's and Home Depot.
warehouse_loc.csv - Geolocated distribution centers.
entry_locv2.csv - Warehouse locations merged with entry locations. Also merged with distance from HQ.
entry_loc3_w_filter.csv - Tries to change geography of the dataset from CDPs to CBSAs

Store locations are often modeled by economists as an "entry game". For more information about this dataset, see the corresponding github repo:
https://github.com/ericschulman/entry_games

Tables

Cbsa

@kaggle.erichschulman_home_improvement_stores.cbsa

45.72 KB
945 rows
6 columns


CREATE TABLE cbsa (
  "n_0" BIGINT,
  "name" VARCHAR,
  "cbsa" BIGINT,
  "b19301_001e" DOUBLE,
  "b01003_001e" BIGINT,
  "metropolitan_statistical_area_micropolitan_statistical_area" BIGINT
);

Census

@kaggle.erichschulman_home_improvement_stores.census

1.04 MB
29573 rows
15 columns


CREATE TABLE census (
  "name" VARCHAR,
  "population" BIGINT,
  "under44_1" DOUBLE,
  "under44_2" DOUBLE,
  "under44_3" DOUBLE,
  "older65_1" DOUBLE,
  "older_65_2" DOUBLE,
  "income_per_capita" DOUBLE,
  "industrial_managers" VARCHAR,
  "construction_managers" VARCHAR,
  "farmers" VARCHAR,
  "realestate" VARCHAR,
  "construction_workers" VARCHAR,
  "state" BIGINT,
  "place" BIGINT
);

Entry

@kaggle.erichschulman_home_improvement_stores.entry

125.09 KB
3672 rows
7 columns


CREATE TABLE entry (
  "store" VARCHAR,
  "address" VARCHAR,
  "city" VARCHAR,
  "state" VARCHAR,
  "zipcode" VARCHAR,
  "url" VARCHAR,
  "time" DOUBLE
);

Entry Loc2

@kaggle.erichschulman_home_improvement_stores.entry_loc2

9.11 MB
17313 rows
70 columns


CREATE TABLE entry_loc2 (
  "unnamed_0_1" BIGINT,
  "unnamed_0" BIGINT,
  "city" VARCHAR,
  "state" BIGINT,
  "hd" BIGINT,
  "low" BIGINT,
  "population" BIGINT,
  "income_per_capita" BIGINT,
  "under44_1" DOUBLE,
  "under44_2" DOUBLE,
  "under44_3" DOUBLE,
  "older65_1" DOUBLE,
  "older_65_2" DOUBLE,
  "stusab" VARCHAR,
  "state_name" VARCHAR,
  "statens" BIGINT,
  "lat" DOUBLE,
  "lon" DOUBLE,
  "low_dist" DOUBLE,
  "hd_dist" DOUBLE,
  "lat_long" VARCHAR,
  "low_mount_vernon" DOUBLE,
  "low_valdosta" DOUBLE,
  "low_rockford" DOUBLE,
  "low_garysburg" DOUBLE,
  "low_findlay" DOUBLE,
  "low_cheyenne" DOUBLE,
  "low_plainfield" DOUBLE,
  "low_statesville" DOUBLE,
  "low_north_vernon" DOUBLE,
  "low_minersville" DOUBLE,
  "low_perris" DOUBLE,
  "low_kissimmee" DOUBLE,
  "hd_hardeeville" DOUBLE,
  "hd_tucson" DOUBLE,
  "hd_lacey" DOUBLE,
  "hd_hialeah" DOUBLE,
  "hd_elk_grove_village" DOUBLE,
  "hd_hiawatha" DOUBLE,
  "hd_south_windsor" DOUBLE,
  "hd_frederick" DOUBLE,
  "hd_fresno" DOUBLE,
  "hd_grove_city" DOUBLE,
  "hd_north_las_vegas" DOUBLE,
  "hd_houston" DOUBLE,
  "hd_alpharetta" DOUBLE,
  "hd_whitestown" DOUBLE,
  "hd_cherry_hill" DOUBLE,
  "hd_loveland" DOUBLE,
  "hd_tulsa" DOUBLE,
  "hd_jenkins_township" DOUBLE,
  "hd_louisville" DOUBLE,
  "hd_waukesha" DOUBLE,
  "hd_hawthorne" DOUBLE,
  "hd_greensboro" DOUBLE,
  "hd_portland" DOUBLE,
  "hd_la_vergne" DOUBLE,
  "hd_suffolk" DOUBLE,
  "hd_huntington" DOUBLE,
  "hd_omaha" DOUBLE,
  "hd_saint_louis" DOUBLE,
  "hd_alabaster" DOUBLE,
  "hd_farmington_hills" DOUBLE,
  "hd_shawnee" DOUBLE,
  "hd_harahan" DOUBLE,
  "hd_saint_paul" DOUBLE,
  "hd_draper" DOUBLE,
  "hd_auburn" DOUBLE,
  "low_warehouse_distance" DOUBLE,
  "hd_warehouse_distance" DOUBLE
);

Entry Loc3 W Filter

@kaggle.erichschulman_home_improvement_stores.entry_loc3_w_filter

65.63 KB
896 rows
15 columns


CREATE TABLE entry_loc3_w_filter (
  "unnamed_0" BIGINT,
  "name" VARCHAR,
  "city" VARCHAR,
  "state" BIGINT,
  "hd" BIGINT,
  "low" BIGINT,
  "population" BIGINT,
  "income_per_capita" BIGINT,
  "stusab" VARCHAR,
  "low_warehouse_distance" DOUBLE,
  "hd_warehouse_distance" DOUBLE,
  "northeast_x" BIGINT,
  "midwest_x" BIGINT,
  "south_x" BIGINT,
  "west_x" BIGINT
);

States

@kaggle.erichschulman_home_improvement_stores.states

4.77 KB
57 rows
4 columns


CREATE TABLE states (
  "state" BIGINT,
  "stusab" VARCHAR,
  "state_name" VARCHAR,
  "statens" BIGINT
);

Warehouse Loc

@kaggle.erichschulman_home_improvement_stores.warehouse_loc

6.1 KB
47 rows
6 columns


CREATE TABLE warehouse_loc (
  "unnamed_0" BIGINT,
  "city" VARCHAR,
  "state" VARCHAR,
  "store" VARCHAR,
  "lat" DOUBLE,
  "lon" DOUBLE
);