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1108 Results
Dataset
Fire Incidents includes a summary of each (non-medical) incident to which the SF Fire Department responded. Each incident record includes the call number, incident number, address, number and type of each unit responding, call type (as determined by dispatch), prime situation (field observation), actions taken, and property loss.
Tags
No tags assigned
Updated
March 26 2023
Views
70,578
A list of officially valid street names contained in the City's GIS Basemap
Updated
March 26 2023
Views
54,592
DEPRECATED
Note: This dataset is now deprecated. The data has been removed. This site will remain until May 4, 2022 to notify users of the new datasets below.
Note: This dataset is now deprecated. The data has been removed. This site will remain until May 4, 2022 to notify users of the new datasets below.
There are two new calls for service datasets
1. Law Enforcement Dispatched Calls for Service: Real-Time (Open calls, updates every 10 min)
2. Law Enforcement Dispatched Calls for Service: Closed (Calls from 2016 to yesterday)
1. Law Enforcement Dispatched Calls for Service: Real-Time (Open calls, updates every 10 min)
2. Law Enforcement Dispatched Calls for Service: Closed (Calls from 2016 to yesterday)
Updated
April 6 2022
Views
52,879
The Health Department has developed an inspection report and scoring system. After conducting an inspection of the facility, the Health Inspector calculates a score based on the violations observed. Violations can fall into:high risk category: records specific violations that directly relate to the transmission of food borne illnesses, the adulteration of food products and the contamination of food-contact surfaces.moderate risk category: records specific violations that are of a moderate risk to the public health and safety.low risk category: records violations that are low risk or have no immediate risk to the public health and safety.The score card that will be issued by the inspector is maintained at the food establishment and is available to the public in this dataset.
San Francisco's LIVES restaurant inspection data leverages the LIVES Flattened Schema (https://goo.gl/c3nNvr), which is based on LIVES version 2.0, cited on Yelp's website (http://www.yelp.com/healthscores).
San Francisco's LIVES restaurant inspection data leverages the LIVES Flattened Schema (https://goo.gl/c3nNvr), which is based on LIVES version 2.0, cited on Yelp's website (http://www.yelp.com/healthscores).
Updated
September 24 2021
Views
47,571
A. SUMMARY
San Francisco International Airport Report on Monthly Passenger Traffic Statistics by Airline.
B. HOW THE DATASET IS CREATED
Data is self-reported by airlines and is only available at a monthly level
C. UPDATE PROCESS
Data updated quarterly
D. HOW TO USE THIS DATASET
Airport data is seasonal in nature, therefore any comparative analyses should be done on a period-over-period basis (i.e. January 2010 vs. January 2009) as opposed to period-to-period (i.e. January 2010 vs. February 2010). It is also important to note that fact and attribute field relationships are not always 1-to-1. For example, Passenger Counts belonging to United Airlines will appear in multiple attribute fields and are additive, which provides flexibility for the user to derive categorical Passenger Counts as desired.
San Francisco International Airport Report on Monthly Passenger Traffic Statistics by Airline.
B. HOW THE DATASET IS CREATED
Data is self-reported by airlines and is only available at a monthly level
C. UPDATE PROCESS
Data updated quarterly
D. HOW TO USE THIS DATASET
Airport data is seasonal in nature, therefore any comparative analyses should be done on a period-over-period basis (i.e. January 2010 vs. January 2009) as opposed to period-to-period (i.e. January 2010 vs. February 2010). It is also important to note that fact and attribute field relationships are not always 1-to-1. For example, Passenger Counts belonging to United Airlines will appear in multiple attribute fields and are additive, which provides flexibility for the user to derive categorical Passenger Counts as desired.
Updated
March 13 2023
Views
44,047
Land use categories for every parcel in San Francisco. The land use categories are derived from a range of City and commercial databases. Where building square footages were missing from these databases they were derived from a LIDAR survey flown in 2007.
Land use categories are as follows (units are square feet):
CIE = Cultural, Institutional, Educational
MED = Medical
MIPS = Office (Management, Information, Professional Services)
MIXED = Mixed Uses (Without Residential)
MIXRES = Mixed Uses (With Residential)
PDR = Industrial (Production, Distribution, Repair)
RETAIL/ENT = Retail, Entertainment
RESIDENT = Residential
VISITOR = Hotels, Visitor Services
VACANT = Vacant
ROW = Right-of-Way
OPENSPACE = Open Space
Other attributes are:
RESUNITS = Residential Units
BLDGSQFT = Square footage data
YRBUILT = year built
TOTAL_USES = Business points from Dun & Bradstreet were spatially aggregated to the closest parcel, and this field is the sum of the square footage fields
The subsequent fields (CIE, MED, MIPS, RETAIL, PDER & VISITOR) were derived using the NAICS codes supplied in the Dun & Bradstreet dataset, and the previous TOTAL_USES column.
The determining factor for a parcel's LANDUSE is if the square footage of any non-residential use is 80% or more of its total uses. Otherwise it becomes MIXED.
In the case where RESIDENT use has some square footage of non-residential use, this is mainly accessory uses such as home businesses, freelancers, etc.
Land use categories are as follows (units are square feet):
CIE = Cultural, Institutional, Educational
MED = Medical
MIPS = Office (Management, Information, Professional Services)
MIXED = Mixed Uses (Without Residential)
MIXRES = Mixed Uses (With Residential)
PDR = Industrial (Production, Distribution, Repair)
RETAIL/ENT = Retail, Entertainment
RESIDENT = Residential
VISITOR = Hotels, Visitor Services
VACANT = Vacant
ROW = Right-of-Way
OPENSPACE = Open Space
Other attributes are:
RESUNITS = Residential Units
BLDGSQFT = Square footage data
YRBUILT = year built
TOTAL_USES = Business points from Dun & Bradstreet were spatially aggregated to the closest parcel, and this field is the sum of the square footage fields
The subsequent fields (CIE, MED, MIPS, RETAIL, PDER & VISITOR) were derived using the NAICS codes supplied in the Dun & Bradstreet dataset, and the previous TOTAL_USES column.
The determining factor for a parcel's LANDUSE is if the square footage of any non-residential use is 80% or more of its total uses. Otherwise it becomes MIXED.
In the case where RESIDENT use has some square footage of non-residential use, this is mainly accessory uses such as home businesses, freelancers, etc.
Last updated: March, 2016
Updated
September 6 2019
Views
42,522
Neighborhood boundaries that were defined in 2006 by the Mayor's Office of Neighborhood Services for use with the SF Find tool: http://propertymap.sfplanning.org/?name=sffind. All boundaries are for the purpose of defining general locations of neighborhoods for the SF FIND application only, and as such they are not "hard" lines of demarcation.
Tags
No tags assigned
Updated
September 6 2019
Views
40,091
Summaries of closed complaints within the Ethics Commission's jurisdiction
Updated
March 10 2023
Views
38,778
This dataset includes police incident reports filed by officers and by individuals through self-service online reporting for non-emergency cases. Reports included are those for incidents that occurred starting January 1, 2018 onward and have been approved by a supervising officer. Please see https://bit.ly/2x7Ta2P for additional documentation.
Disclaimer: The San Francisco Police Department does not guarantee the accuracy, completeness, timeliness or correct sequencing of the information as the data is subject to change as modifications and updates are completed.
Tags
No tags assigned
Updated
March 25 2023
Views
38,184
A. SUMMARY
The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013.
The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013.
B. HOW THE DATASET IS CREATED
This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format.
This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format.
C. UPDATE PROCESS
New data is added on a bi-annual basis when available for each fiscal and calendar year.
New data is added on a bi-annual basis when available for each fiscal and calendar year.
D. HOW TO USE THIS DATASET
Before using please first review the following two resources:
Data Dictionary - Can be found in 'About this dataset' section after click 'Show More'
Employee Compensation FAQ - https://support.datasf.org/help/employee-compensation-faq
Before using please first review the following two resources:
Data Dictionary - Can be found in 'About this dataset' section after click 'Show More'
Employee Compensation FAQ - https://support.datasf.org/help/employee-compensation-faq
Updated
March 20 2023
Views
38,067