Demographics, population, housing, income, education, schools, and geography for ZIP Code 94111 (San Francisco, CA). Interactive charts load automatically as you scroll for improved performance.

Dataset

This dataset was created by Helen Gavrouchenko

Released under World Bank Dataset Terms of Use

Contents

A. SUMMARY This dataset contains the list of intersecting Analysis Neighborhoods and ZIP Codes for the City and County of San Francisco. It can be used to identify which ZIP codes overlap with Analysis Neighborhoods and vice verse. B. HOW THE DATASET IS CREATED The dataset was created with a spatial join between the Analysis Neighborhoods and ZIP codes. C. UPDATE PROCESS This is a static dataset D. HOW TO USE THIS DATASET This dataset is a many-to-many relationship between analysis neighborhoods and ZIP codes. A single neighborhood can contain or intersect with multiple ZIP codes and similarly, a single ZIP code can be in multiple neighborhoods. This dataset does not contain geographic boundary data (i.e. shapefiles/ GEOMs). The datasets below containing geographic boundary data should be used for analysis of data with geographic coordinates. E. RELATED DATASETS Analysis Neighborhoods San Francisco ZIP Codes Supervisor District (2022) to ZIP Code Crosswalk Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods

San Francisco ZIP Code Areas. Matched to city streets and lots by Department of Planning. These are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. Please note that actual USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes.

As of November 2023, this map has been updated to use a new format. For details, please see here.
San Francisco ZIP Code Areas. Matched to city streets and lots by Department of Planning. These are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. Please note that actual USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes.

Bay Area ZIP Codes

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Content

Lists intersecting Supervisor Districts and ZIP Codes for City and County of San Francisco.

Context

This is a dataset hosted by the city of San Francisco. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore San Francisco's Data using Kaggle and all of the data sources available through the San Francisco organization page!

• Update Frequency: This dataset is updated quarterly.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Tomas Sobek on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

A. SUMMARY Medical provider confirmed COVID-19 cases and confirmed COVID-19 related deaths in San Francisco, CA aggregated by Census ZIP Code Tabulation Areas and normalized by 2018 American Community Survey (ACS) 5-year estimates for population data to calculate rate per 10,000 residents.

Cases and deaths are both mapped to the residence of the individual, not to where they were infected or died. For example, if one was infected in San Francisco at work but lives in the East Bay, those are not counted as SF Cases or if one dies in Zuckerberg San Francisco General but is from another county, that is also not counted in this dataset.

Dataset is cumulative and covers cases going back to March 2nd, 2020 when testing began. It is updated daily.

B. HOW THE DATASET IS CREATED Addresses from medical data are geocoded by the San Francisco Department of Public Health (SFDPH). Those addresses are spatially joined to the geographic areas. Counts are generated based on the number of address points that match each geographic area. The 2018 ACS estimates for population provided by the Census are used to create a rate which is equal to ([count] / [acs_population]) * 10000) representing the number of cases per 10,000 residents.

C. UPDATE PROCESS Geographic analysis is scripted by SFDPH staff and synced to this dataset each day.

D. HOW TO USE THIS DATASET Privacy rules in effect To protect privacy, certain rules are in effect: 1. Case counts greater than 0 and less than 10 are dropped - these will be null (blank) values 2. Cases dropped altogether for areas where acs_population < 1000

Rate suppression in effect where counts lower than 20 Rates are not calculated unless the case count is greater than or equal to 20. Rates are generally unstable at small numbers, so we avoid calculating them directly. We advise you to apply the same approach as this is best practice in epidemiology.

A note on Census ZIP Code Tabulation Areas (ZCTAs) ZIP Code Tabulation Areas are special boundaries created by the U.S. Census based on ZIP Codes developed by the USPS. They are not, however, the same thing. ZCTAs are polygonal representations of USPS ZIP Code service area routes. Read how the Census develops ZCTAs on their website.

This dataset is a filtered view of another dataset You can find a full dataset of cases and deaths summarized by this and other geographic areas.

E. CHANGE LOG

• 9/11/2023 - data on COVID-19 cases and deaths summarized by ZIP code tabulation area are no longer being updated. This data is currently through 9/6/2023 and will not include any new data after this date.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

View the 2022 Zip Code to Supervisor District Crosswalk: https://data.sfgov.org/Geographic-Locations-and-Boundaries/Supervisor-District-2022-to-ZIP-Code-Crosswalk/2x22-z5j6

Lists intersecting Supervisor Districts and ZIP Codes for City and County of San Francisco.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. The Address Range / Feature Name Relationship File (ADDRFN.dbf) contains a record for each address range / linear feature name relationship. The purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute that can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature name is identified by the linear feature identifier (LINEARID) attribute that can be used to link to the Feature Names Relationship File (FEATNAMES.dbf).

A. SUMMARY This dataset contains the list of intersecting 2022 Supervisor Districts and ZIP Codes for the City and County of San Francisco. It can be used to identify which ZIP codes overlap with Supervisor Districts (2022) and vice verse.

B. HOW THE DATASET IS CREATED The dataset was created with a spatial join between the 2022 Supervisor districts and ZIP codes.

C. UPDATE PROCESS This is a static dataset

D. HOW TO USE THIS DATASET This dataset is a many-to-many relationship between supervisor districts and ZIP codes. A single supervisor district can contain or intersect with multiple ZIP codes and similarly, a single ZIP code can be in multiple supervisor districts. This dataset does not contain geographic boundary data (i.e. shapefiles/ GEOMs). The datasets below containing geographic boundary data should be used for analysis of data with geographic coordinates.

E. RELATED DATASETS Supervisor Districts (2022) San Francisco ZIP Codes Supervisor District (2012) to ZIP Code Crosswalk Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods

The table below showcases the total number of homes sold for each zip code in South San Francisco, California. It's important to understand that the number of homes sold can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in South San Francisco, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The median house prices in the most expensive zip codes in California reached as high as *** million U.S dollars. Atherton (94027), had the most expensive median house price, followed by Santa Barbara (93108), and Beverly Hills (90210). Six of the ranked zip codes were among the top ten most expensive zip codes in the United States in 2023.

This polygon shapefile displays landmark features throughout the San Francisco Bay Area in California. "Landmark" is the general name given to a cartographic (or locational) landmark, a land-use area, and a key geographic location (KGL). A cartographic landmark is identified for use by an enumerator while working in the field. A land-use area is identified in order to minimize enumeration efforts in uninhabited areas or areas where human access is restricted. A key geographic location is identified in order to more accurately geocode and enumerate a place of work or residence. The predominant feature classes represented in this layer include airports or airfields, cemeteries, fraternities or sororities, state or local parks or forests, golf courses, lookout towers, educational and religious institutions. Other possible landmark features could include military installations, multi-household or transient quarters, custodial facilities, other types of transportation facilities or terminals, employment centers, open space and other special landmark designations for post offices, police stations and firehouses. The Census Bureau includes landmarks in the Census TIGER data base for locating special features and to help enumerators during field operations. The Census Bureau added landmark features on an as-needed-basis and made no attempt to ensure that all instances of a particular feature were included. The absence of a landmark does not mean that the living quarters, e.g., hospitals and group quarters associated with the landmark were excluded from the 1990 enumeration. A census feature class code (CFCC) is used to identify the most noticeable characteristic of a feature. The CFCC is applied only once to a chain or landmark with preference given to classifications that cover features that are visible to an observer and a part of the ground transportation network. Thus, a road that also is the boundary of a town would have a CFCC describing its road characteristics, not its boundary characteristics. The CFCC, as used in the TIGER/Line files, is a three-character code. The first character is a letter describing the feature class; the second character is a number describing the major category; and the third character is a number describing the minor category. Landmark (Feature Class D) is the general name given to a cartographic (or locational) landmark, a land-use area, and a key geographic location. This layer is part of the Bay Area Metropolitan Transportation Commission (MTC) GIS Maps and Data collection.

This dataset contains information about calls to the Fire Department of San Francisco to ask for intervention. The dataset provides details on the time of the calls, the San Francisco area where they came from, and so on.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

A. SUMMARY This dataset contains sales tax collected in San Francisco for calendar years 2015 through the quarter preceding the most recent one. Sales tax is aggregated, or summed, using Zip Code boundaries. However, some geographic boundaries have been combined to maintain the anonymity of businesses based on Taxation Code Section 7056. See “How to use this dataset” below for more details on how the data has been aggregated. Sales tax is collected by businesses on many types of transactions and regulated by the California Department of Tax and Fee Administration.

B. HOW THE DATASET IS CREATED Data is collected by HDL. The data is then aggregated based on the criteria outlined in the "How to use this dataset" section.

C. UPDATE PROCESS This dataset will be updated quarterly.

D. HOW TO USE THIS DATASET This dataset can be used to analyze sales tax data over time across geographic boundary in San Francisco. Due to data privacy protection regulations for businesses, sales tax data is not available for all geographic boundary. For example, boundaries where there are less than 4 businesses paying sales tax or a single business that pays 80% or more of the total sales tax have been combined with neighboring geographic boundary to protect the confidentiality of affected businesses.

Because of this aggregation, some Zip Code groups in this dataset may change in future years as the number of businesses in a particular Zip Code change. The historical data changes based on audit findings and amended returns. If Zip Code groupings change, it will happen when the dataset is updated - on a quarterly basis. These new blocks will be backfilled to previous years. Additionally, business payers with multiple locations (for example chain stores) are excluded because sales tax cannot be tied back to the location where it was collected.

E. RELATED DATASETS Sales Tax by Supervisor District Sales Tax by Census Block Sales Tax by Analysis Neighborhood Sales Tax by Zip Code