Data files pertaining to staff demographics, credentials and teaching load.
cde.ca.gov-staff-1.1.2
. Modified 2022-06-27T23:03:03
Resources | Packages | Documentation| Contacts| References| Data Dictionary
Resources
- staff_cred. Staff credentials
- staff_demo. Staff Demographics
- staff_fte. Staff FTE teaching load 100=full time.
Documentation
License
The upstream data, from the California Department of Education, does not explicitly reference a license, so we assume it is in the public domain.
License
The source data, from the California Department of Education, does not
explicitly reference a license, but since the top-level website for California
indicates that data published on the State of California website is
generally in the public domain, we assume it is in
the public domain. Derived data included in this package is also in the public domain. Metadata in this package ( contained in the metadata.csv
file ) is
derived from metadata for the source package, and is also in the public domain.
Programs used for data transformation (contained in the notebooks
directory), are Copyright 2021 Civic Knowledge, and
are relased under the Creative Commons Attribution-ShareAlike 4.0 International
License.
Documentation Links
- StaffData-EntityRelationshipDiagram ERD diagram for the relationships within the data files.
- Staff Demographics 2015-16 to Current File structure for the staff demographics record, which includes demographic and full-time equivalent (FTE) data for K-12 public education certificated teachers, administrators, and pupil services personnel reported as employed on Information Day.
- Staff Credentials 2012–13 to Current File structure for staff credential data, including associated authorizations, for staff employed on Information Day.
- Staff School FTE 2012–13 to Current This table contains the structure for the staff school FTE record.
- Documentation Page
Contacts
- Wrangler
Data Dictionary
staff_cred | staff_demo | staff_ftestaff_cred
Column Name | Data Type | Description |
---|---|---|
academicyear | integer | |
recid | integer | |
credentialtype | integer | |
authorizationtype | integer | |
filecreated | date |
staff_demo
Column Name | Data Type | Description |
---|---|---|
academicyear | integer | |
recid | integer | |
districtcode | integer | |
countyname | string | |
districtname | string | |
gendercode | string | |
educationlevel | string | |
ethnicgroup | integer | |
yearsteaching | integer | |
yearsindistrict | integer | |
employmentstatuscode | string | |
fte_teaching | number | |
fte_administrative | number | |
fte_pupilservices | number | |
filecreated | date | |
age | number |
staff_fte
Column Name | Data Type | Description |
---|---|---|
academicyear | integer | |
recid | integer | |
districtcode | integer | |
schoolcode | integer | |
countyname | string | |
districtname | string | |
schoolname | string | |
jobclassification | integer | |
stafftype | string | |
fte | number | |
filecreated | date |
References
Urls used in the creation of this data package.
- StaffCred12.
- StaffCred13.
- StaffCred14.
- StaffCred15.
- StaffCred16.
- StaffCred17.
- StaffCred18.
- StaffDemo12.
- StaffDemo13.
- StaffDemo14.
- StaffDemo15.
- StaffDemo16.
- StaffDemo17.
- StaffDemo18.
- StaffSchoolFTE12.
- StaffSchoolFTE13.
- StaffSchoolFTE14.
- StaffSchoolFTE15.
- StaffSchoolFTE16.
- StaffSchoolFTE17.
- StaffSchoolFTE18.
Packages
- s3 s3://library.metatab.org/cde.ca.gov-staff-1.1.2.csv
- csv http://library.metatab.org/cde.ca.gov-staff-1.1.2.csv
- source https://github.com/metatab-packages/cde.ca.gov-collection.git
Accessing Data in Vanilla Pandas
import pandas as pd
staff_cred_df = pd.read_csv('http://library.metatab.org/cde.ca.gov-staff-1.1.2/data/staff_cred.csv')
staff_demo_df = pd.read_csv('http://library.metatab.org/cde.ca.gov-staff-1.1.2/data/staff_demo.csv')
staff_fte_df = pd.read_csv('http://library.metatab.org/cde.ca.gov-staff-1.1.2/data/staff_fte.csv')
Accessing Package in Metapack
import metapack as mp
pkg = mp.open_package('http://library.metatab.org/cde.ca.gov-staff-1.1.2.csv')
# Create Dataframes
staff_cred_df = pkg.resource('staff_cred').dataframe()
staff_demo_df = pkg.resource('staff_demo').dataframe()
staff_fte_df = pkg.resource('staff_fte').dataframe()