pnt 0.0.4

A simple tool for generating and analyzing bibliometric citation network data from Pubmed.

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PubMed Network Toolkit (pnt)

pnt is a simple Python package for extracting and analyzing bibliometric citation network data from PubMed. The package is designed to support:

• pulling citation metadata from PubMed;
• constructing co-authorship networks;
• generating edge and node lists;
• visualizing basic network structures.

Author: Jacob Rohde ([e-mail])

Release notes: Version 0.0.2 (released 2025-05-20) added a sub-package library with functions for filtering and summarizing PubMed data sets using locally hosted language models via Ollama. This package is released under the MIT license.

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Package overview

GetPubMedData()

A class object for extracting a citation data set from PubMed using Metapub.

pnt.GetPubMedData(search_term, 
                  pubmed_api_key=None, 
                  size=250, 
                  start_date=None, 
                  end_date=None)

Arguments/attributes:

• search_term
  The only required argument. Takes a single string as a search term(s).
  Example:

  search_term='cancer' 
  search_term='cancer and tobacco' 
  

• pubmed_api_key (optional)
  A string argument to specify a PubMed NCBI API key. If set, this key is registered as an environment variable, reducing API rate limiting.

• size (optional)
  An integer that indicates how many PubMed citations to retrieve. Default is 250.
  Note: This class is intended for small-scale or exploratory data pulls.

• start_date / end_date (optional)
  String parameter(s) to specify the date range for citation retrieval. Default end_date set to current date. Format: 'YYYY, MM, DD' (e.g., '2023, 01, 01')

• GetPubMedData.citation_df
  A pandas DataFrame containing the citation data. The DataFrame includes the following columns: 'pmid', 'first_author', 'last_author', 'author_list', 'title', 'journal', 'year', 'volume', 'issue', 'pages', 'url', 'abstract', 'citation', 'doi'

• GetPubMedData.write_data()
  Saves the citation DataFrame to file. Accepts the following optional keyword arguments:

  • file_type: Format to save the file. Accepts 'csv' or 'json'. Default is 'csv'.
  • file_name: Name of the output file (without extension). Default is the provided search_term.

pnt.GetCitationNetwork()

A class object for generating edge and node lists, and a NetworkX graph object from a PubMed citation data set.

pnt.GetCitationNetwork(citation_dataset, 
                       edge_type='directed')

Arguments/attributes:

• citation_dataset
  The only required argument. Takes an existing citation data set or a GetPubMedData object.

• edge_type (optional)
  String argument set to either 'directed' or 'undirected', to signify network edge type; default is 'directed'.

• GetCitationNetwork.edge_list
  Returns a pandas DataFrame of the network edge list with columns for source author, target co-author, and the journal.

• GetCitationNetwork.node_list
  Returns a pandas DataFrame of the network node list with columns for unique nodes, degree, and the node's associated journals.

• GetCitationNetwork.graph
  Returns a NetworkX graph object.

• GetCitationNetwork.write_data()  Object method that writes edge_list and node_list data sets to file. Accepts the same optional arguments as GetPubMedData.write_data() (i.e., 'file_type' and 'file_name').

single_network_plot()

A simple function for plotting networks via NetworkX and Matplotlib (additional install required). Please note this function is currently a work in progress and is meant to be basic tool to plot a single graph. See NetworkX documentation for more advanced plotting needs.

pnt.single_network_plot(network, **kwargs)

Arguments:

• network
  The only required argument. Takes a GetCitationNetwork or NetworkX graph object.

• title(optional)
  String argument to add a title to the plot.

• pos(optional)
  String argument to set the NetworkX plotting algorithm. For ease of use, the argument currently accepts one of the following layout types as a string: 'spring_layout' (default), 'kamada_kawai_layout', 'circular_layout', or 'random_layout'

• kwargs(optional)
  The function also accepts several other NetworkX keyword arguments for plotting (please see NetworkX documentation for more info on these arguments). Currently accepted arguments include:

  • 'arrows' (bool)
  • 'arrowsize' (int)
  • 'edge_color' (str or list/array)
  • 'font_size' (int)
  • 'node_color' (str or list/array)
  • 'node_size' (str or list/array)
  • 'verticalalignment' (str)
  • 'width' (int/float or list/array)
  • 'with_labels' (bool)

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Example use case for pnt

This example demonstrates how to use pnt to:

1. Extract a PubMed citation data set.
2. Write the citation data to file.
3. Construct a citation network graph from the data.
4. Plot the citation network using Matplotlib.
5. Write the resulting edge list, node list, and adjacency matrices to file.

import pnt  # Assumes pnt is installed 

# Extract citation data for the keyword topic 'tobacco control'
pubmed_data = pnt.GetPubMedData(search_term='tobacco control',
                                size=25, 
                                start_date='2025, 1, 1',
                                end_date='2025, 1, 31')

# Access the resulting data set 
df = pubmed_data.citation_df
print(df)

# Write the data to CSV
pubmed_data.write_data(file_type='csv', file_name='tob_control_citations')

# Create a citation network object from the data 
network = pnt.GetCitationNetwork(pubmed_data, edge_type='directed')

# Plot the citation network 
pnt.single_network_plot(network=network,
                        title='Example tobacco control co-citation network plot',
                        arrows=True,
                        with_labels=True)

# Access the edge and node lists and save the data to file
edge_df = network.edge_list
node_df = network.node_list
network.write_data(file_type='csv', file_name='citation_network')

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Requirements

• Python 3.XX
• metapub - a Python library with functions to query the PubMed API
• numpy - a Python library for handling arrays and matrices
• pandas - a Python library for data management
• NetworkX - a Python library for network analysis
• Matplotlib (only if using the single_network_plot() function) - a Python library for plotting

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