A Python package for working with IPEDS data.
Read the full documentation here.
# with pip
pip install ipeds
From the shell:
scipeds download-db
or from python / a notebook:
import scipeds
scipeds.download_db()
from scipeds.data.completions import CompletionsQueryEngine
from scipeds.data.queries import (
FieldTaxonomy,
QueryFilters,
)
engine = CompletionsQueryEngine()
Use a pre-baked query:
gender_df = engine.field_totals_by_grouping(
grouping="gender",
taxonomy=FieldTaxonomy.ncses_field_group
)
or write your own using duckdb SQL syntax:
from scipeds.constants import COMPLETIONS_TABLE
df = engine.get_df_from_query(f"""
SELECT *
FROM {COMPLETIONS_TABLE}
LIMIT 10;
""")
For more detailed usage, see the Usage page or the engine API Reference.
scipeds
is a Python package for working with data from IPEDS. Specifically, scipeds
makes it easier for people to analyze data from IPEDS by pre-processing and standardizing IPEDS data into a database and providing some Python tooling for querying that database.
scipeds
is not a tool for working with raw IPEDS data. For that, you should download data directly from IPEDS.
Full scipeds
documentation can be found at this link, and the source code is avilable on GitHub.
scipeds
currently supports the following datasets / survey components:
- IPEDS Completions by program (6-digit CIP code), award level, race/ethnicity, and gender from 1995-2023
- IPEDS Institutional Characteristics Directory Information from 2011-2023
We provide functionality to reproduce our pre-processing of the IPEDS data. To recreate the pre-processed database, you can clone the scipeds
repository, download the raw data, and re-run the pipeline code in pipeline/
. Decisions about how to convert / crosswalk data across different years and handle other edge cases such as missing data are contained in the pipeline code.
While IPEDS provides a large volume of data about higher education in the United States, working with IPEDS data can be challenging! Many things have changed in the time that data has been reported to IPEDS, making it non-trivial to join datasets across different time periods to consistently measure changes over time.
In the process of their own work, the authors found it useful to create tools to make it easier to analyze IPEDS data and hoped that the tools they created would be useful to others as well.
scipeds
was created by Science for America as part of its mission to address urgent challenges in STEM education.