San Diego Business Clusters – SDRDL Data Repository

Business in San Diego linked to entertainment clusters and population density.

sandiegodata.org-business_clusters-1.1.5. Modified 2021-03-21T19:41:52

Resources

sb_mbl. Businesses registered in San DIego, from the Master BusinessList
sd_business_clusters. Geographic boundaries of business clusters
sd_businesses. San Diego Businesses, geocoded
sd_custered_businesses. San Diego Businesses, geocodes and linked to clusters.
naics. Naics codes for San Diego businesses

Documentation

This dataset processes the City of San Diego Master Business file to add geocoded addresses and links to business clusters. San Diego publishes two lists of businesses, which are based on payment of the San Diego City business tax: the Master Business File, and a SANGIS file that includes geographic information. Unfortunatel y, these files are quite different and cannot be linked. The SANGIS file is oriented toward the tax assessors parcel that the business occupies, and the Master Business List has account numbers and addresses, but there is no common key between the files.

The files in this package add address geocodes to the Master Business List, and links the businesses to clusters of businesses. The Clusters are created by collecting nearby businesses from Open Street Map data. The cluster types are:

NA: No cluster, 31787 businesses
shop: OSM tags ‘shop’, ‘clothes’, ‘supermarket’, ‘bank’, ‘laundry’, ‘parking’, 14615 businesses
ent: Entertainment, OSM tags ‘cafe’, ‘restaurant’, ‘bar’, 14320 businesses
casual: Fast food and convenience stores, OSM tags ‘fast_food’, ‘convenience’, 10991 businesses

The sd_business_clusters file has the clusters and their WKT geographies. The sd_custered_businesses links San Diego businesses to clusters, and a single business may be in more than one cluster because the clusters of different tyoes overlap.

NAICS Codes

It appears that the NAICS codes used in the Master Business List are vintage 2007. The code ‘72221’ appears frequently, which is valid in 2007 NAICS, but not in 2012 or 2016 NAICS.

Geocoding

The geocoding was performed with a local installation of Pelias. There are some notable errors in the geocoding. For instance, Ba Ho Liquor and Deli, with address of ‘4031 AVATI DR SUITE I SAN DIEGO 92117-4403, CA’, was geocoded to 4144 Avati, moving the location from a neighborhood mini-mall to a residence. It is unknown how many such error there are, so use the geocodes with caution.

Documentation Links

Documentation Page

Contacts

Wrangler
Eric Busboom, Civic Knowledge

Data Dictionary

sb_mbl | sd_business_clusters | sd_businesses | sd_custered_businesses | naics

sb_mbl

Column Name	Data Type	Description
business_acct	integer
dba_name	string
ownership_type	string
address	string
city	string
zip	string
state	string
business_phone	string
owner_name	string
creation_dt	date
start_dt	date
exp_dt	date
naics	integer	2007 NAICS code
activity_desc	string

sd_business_clusters

Column Name	Data Type	Description
cluster_n	integer	Cluster number
cluster_type	string	Cluster type: ent, shop, or casual
geometry	string

sd_businesses

Column Name	Data Type	Description
account	integer
gc_address	string	Address used for geocoding
lat	number	Geocoded latitude
lon	number	Geocoded longitude
dba_name	string
ownership_type	string
creation_dt	date
start_dt	date
exp_dt	date
owner_name	string
naics	integer
activity_desc	string
geometry	string	Geocoded position, in WKT format
geoid	string	Geoid of the Census block group that contain the business point.
pop	integer	Population of the bock group, from 2019 5 year ACS
area	integer	Area of the block group in square meters.

sd_custered_businesses

Column Name	Data Type	Description
account	integer
gc_address	string
lat	number
lon	number
geoid	string
pop	integer
area	integer
dba_name	string
ownership_type	string
creation_dt	date
start_dt	date
exp_dt	date
owner_name	string
naics	integer
activity_desc	string
cluster_n	integer	Cluster number
cluster_type	string	Cluster type: ent, shop, or casual
geometry	string	Point location of the business, in WKT format

naics

Column Name	Data Type	Description
account	integer	Business account number
naics	integer	Full NAICS code
naics_2	integer	2 digit NAICS prefix
naics_3	integer	3 digit NAICS prefix
naics_4	integer	4 digit NAICS prefix
naics_5	integer	5 digit NAICS prefix
naics_6	integer	6 digit NAICS prefix
naics_desc	string	Description of the NAICS code
naics_2_desc	string
naics_3_desc	string
naics_4_desc	string
naics_5_desc	string
naics_6_desc	string

References

Urls used in the creation of this data package.

index:civicknowledge.com-osm-demosearch-2.1.1#business_clusters. US business clusters
sd_businesses_ak. San Diego Businesses A-K
sd_businesses_lz. San Diego Businesses L-Z
metapack+http://library.metatab.org/sangis.org-business_sites.csv#business_sites. San DIego Business locations, from SANGIS
metapack+http://library.metatab.org/sandiegodata.org-geography-2018-13.csv#sd_county_boundary. San Diego County Geo boundry
naics_index_2007. NAICS index file, 2007.
naics_index_2007_26. NAICS index file, 2007, 2 to 6 digit codes
censusgeo://2019/5/CA/blockgroup. CA Census Blocks
census://2019/5/CA/blockgroup/B01003. Total population by blocks

Packages

s3 s3://library.metatab.org/sandiegodata.org-business_clusters-1.1.5.csv
csv http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5.csv
source https://github.com/CivicKnowledge/radius-search.git

Accessing Data in Vanilla Pandas

import pandas as pd


sb_mbl_df =  pd.read_csv('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5/data/sb_mbl.csv')
sd_business_clusters_df =  pd.read_csv('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5/data/sd_business_clusters.csv')
sd_businesses_df =  pd.read_csv('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5/data/sd_businesses.csv')
sd_custered_businesses_df =  pd.read_csv('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5/data/sd_custered_businesses.csv')
naics_df =  pd.read_csv('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5/data/naics.csv')

Accessing Package in Metapack

import metapack as mp
pkg = mp.open_package('http://library.metatab.org/sandiegodata.org-business_clusters-1.1.5.csv')

# Create Dataframes
sb_mbl_df = pkg.resource('sb_mbl').dataframe()
sd_business_clusters_gdf = pkg.resource('sd_business_clusters').geoframe()
sd_businesses_gdf = pkg.resource('sd_businesses').geoframe()
sd_custered_businesses_gdf = pkg.resource('sd_custered_businesses').geoframe()
naics_df = pkg.resource('naics').dataframe()