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        "author": "Brian Austin",
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        "description": "# Grandas\n\nGrandas as a library that allows simplified, flexible analysis of the nodes and relationships stored in a graph database. It allows a user to search for and filter information and connections contained in a subgraph of a graph database.\n\n## Data Structures\n### Node\nA Node object is the basic entity object and identifies any noun in your graph dataset.\n\n\n### Relationship\nA Relationship stores the way that any two nodes in your dataset are related. Bi-directional relationships here are stored as two independent relationships.\n\n### NodeFrame\nNodeframes allow users to see the nodes in their graph databases, and further enable them to filter and resolve redundant nodes.\n\n### RelationshipFrame\nThe RelationshipFrame object stores a series of Relationship objects as a pandas DataFrame, using the hashed value of the full node to identify where the start and ending points for each relationship are.\n\n### GraphFrame\nA GraphFrame is comprised of a NodeFrame (attribute: `nodes`) and a RelationshipFrame (attribute: `rels`).\n\n---\n## Getting Started\nTo get started using grandas, you can install it using pip:\n```\npip install grandas\n```\n\nFrom there, load in nodes and relationships to a GraphFrame object, similar to how you would use a pandas DataFrame.\n\n```\nimport grandas as gd\n\nnodes = [\n  Node(label='PERSON',name='Alice',age='27'),\n  Node(label='PERSON',name='Bob',age='24'),\n  ]\nalice, bob = nodes\nrels = [\n  Relationship(start=alice, end=bob, label='owes_money_to',amount=10)\n]\ngf = GraphFrame(nodes=nodes, relationships=rels)\n\nnode_frame = gf.nodes\nrelationship_frame =  gf.rels\n```\n\n\n---\n## Contributing\nContributions are more than welcome! Please just submit a pull request to the `develop` branch.",
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