NBDT_datasets

A Comprehensive Library for Research Paper Recommendation and Dataset Management

Installation

For installation, you can run the following code in the command line/terminal:

git clone https://github.com/nbdt-journal/nbdt_lib.git
pip install ./nbdt_lib

Load Datasets

Currently the library has 5 datasets ready to use:

arxiv: Has nearly 3.5k papers

bioarxiv: Has 29k papers from Bioarxiv

plos_one: Has 18k papers from PLOS_ONE

medline_small: Has 105k papers from the top 200 journals in the neuroscience field

medline_large: Has 200k papers from MEDLINE

To load your dataset use the following code:

from nbdt.datasets import load_dataset
load_dataset(dataset_name = 'arxiv', destination_path = 'arxiv.csv', start_year = 2018, end_year = 2023)

If destination_path is not specified, the dataset will be loaded as a pandas DataFrame to the specified variable.
If start_year and end_year are not specified, the entire dataset is returned by default.
Only papers with a publishing year from 2018 to 2023 are available in all specified datasets.

Update Datasets

To update your dataset, use the following code:

from nbdt.update import update_dataset
update_dataset(dataset_name, start_date, end_date, destination_path, update)

# Examples
update_dataset(dataset_name='plos_one', start_date='06-2023', end_date = '08-2023', destination_path='plos_one_new.csv', update=True)
update_dataset(dataset_name='bioarxiv', end_date = '08-2023', destination_path='bioarxiv_new.csv') # Here as 'update' and 'start_date' is not specified, their respective default values are applied, e.g False and 01-01-2023.

dataset_name: Currently only arxiv, bioarxiv, and plos_one datasets are available for updation.

start_date and end_date: The input of both the parameters should be in MM-YYYY, any other format will return an error. By default all the datasets are updated to a predefined start date:

arxiv: 31-05-2023
bio_arxiv: 01-01-2023
plos_one: 31-05-2023

destination_path: Specify the destination path as required, for example: '/content/arxiv.csv' (Note: The file format should be in CSV)

update: By default, this parameter is False, but if update=True is passed then the source dataset along with the updated data of the mentioned period will be returned to the specified destination path.

Note: The parameters dataset_name, destination_path, and end_date should be atleast specified to return any data.

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