datanest 1.0.0

A simple, intuitive, pandas-based database.

datanest

A simple, intuitive, pandas-based database.

Perfect for handling data such as time series, images, or any Python objects alongside their metadata. This tool encapsulates a pandas DataFrame containing metadata and Python objects. It provides an intuitive data and metadata retrieval syntax through keyword-arguments.

---

Installation

pip install datanest

Usage

datanest.Database is the core class that wraps a pandas.DataFrame object. Even before adding any data fields using the add_data_field method, the database can already be used to query rows from the encapsulated DataFrame with an intuitive keyword argument syntax.

import datanest

# Load example DataFrame with columns: 
# participant_id (int), age (float), surgery_performed (bool), notes (str)
db = datanest.get_example_database()

# Retrieve all metadata
db()

# Retrieve metadata for participant 3
db(participant_id=3)

# Retrieve metadata for participants aged 50 to 60 who have not had surgery
db(age_lim=(50, 60), surgery_performed=True)

# Retrieve metadata for participants where the notes string contains the word interesting
db(notes_has='interesting')

The add_data_field method can be used to add arbitrary python objects to the database, and we can retrieve relevant data entries using the same keyword argument syntax.

# Add heart rate data to the database, indexed by participant_id
db.add_data_field('heart_rate', datanest.get_example_data(), 'participant_id')

# Retrieve all heart rate time series data
db.heart_rate()

# Retrieve heart rate time series data for participant 3
db.heart_rate(participant_id=3)

# Retrieve heart rate time series for participants aged 50 to 60
db.heart_rate(age_lim=(50, 60))

# Retrieve heart rate time series for participants where the notes string contains the word interesting
db.heart_rate(notes_has='interesting')

License

datanest is distributed under the terms of the MIT license.

Contact

Praneeth Namburi

Project Link: https://github.com/praneethnamburi/datanest

Acknowledgments

This tool was developed as part of the ImmersionToolbox initiative at the MIT.nano Immersion Lab. Thanks to NCSOFT for supporting this initiative.