¶
A Python package for working with IPEDS data.
A Python package for working with IPEDS data.
Read the full documentation here.
Quickstart¶
Option 1: Use Colab (no installation required)¶
Click the link below to launch a pre-configured Google Colab notebook for scipeds:
Open the Colab notebook using the link above (also here), and then follow the instructions in the notebook to explore and use scipeds in a cloud environment. This approach does not require you to install anything on your computer.
If you want to keep using scipeds this way, you'll need to make a copy of the notebook into your own Google Drive.
Option 2: Install scipeds on your computer¶
Alternatively, you can install scipeds on your own computer and work from there.
Install scipeds¶
Open a terminal and type:
pip install scipeds
Download the pre-processed database¶
You can download the pre-processed database in two ways.
Either from the shell:
scipeds download-db
or from within python (i.e. in a Python interactive shell or from a notebook):
import scipeds
scipeds.download_db()
Query completions data using the corresponding query engine¶
Now you are ready to try scipeds's functionality!
For example, you can look at completions data by gender:
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,
query_filters=QueryFilters()
)
gender_df.head()
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;
""")
df.head()
For more detailed usage, see the Usage page or the engine API Reference.
About scipeds¶
What is scipeds?¶
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 available on GitHub.
Currently supported IPEDS surveys¶
scipeds currently supports the following datasets / survey components:
- IPEDS Completions by program (6-digit CIP code), award level, race/ethnicity, and gender from 1984-2023
- IPEDS Institutional Characteristics Directory Information from 2011-2023
Completions data preprocessing¶
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.
Why does scipeds exist?¶
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.
Who created scipeds?¶
scipeds was created by Science for America (in collaboration with DrivenData) as part of its mission to address urgent challenges in STEM education.
The scipeds logo was designed by Adrianna Mena.