awswrangler.neptune.to_property_graph

awswrangler.neptune.to_property_graph(client: NeptuneClient, df: DataFrame, batch_size: int = 50, use_header_cardinality: bool = True) → bool

Write records stored in a DataFrame into Amazon Neptune.

If writing to a property graph then DataFrames for vertices and edges must be written separately.

DataFrames for vertices must have a ~label column with the label and a ~id column for the vertex id. If the ~id column does not exist, the specified id does not exist, or is empty then a new vertex will be added.

DataFrames for edges must have a ~id, ~label, ~to, and ~from column. If the ~id column does not exist the specified id does not exist, or is empty then a new edge will be added.

Existing ~id values will be overwritten. If no ~id, ~label, ~to, or ~from column exists, an InvalidArgumentValue exception will be thrown.

If you would like to save data using single cardinality then you can postfix (single) to the column header and set use_header_cardinality=True (default). e.g. A column named name(single) will save the name property as single cardinality. You can disable this by setting use_header_cardinality=False.

Parameters:

  • client (NeptuneClient) – instance of the neptune client to use

  • df (DataFrame) – Pandas DataFrame

  • batch_size (int) – The number of rows to save at a time. Default 50

  • use_header_cardinality (bool) – If True, then the header cardinality will be used to save the data. Default True

Return type:

bool

Returns:

True if records were written

Examples

Writing to Amazon Neptune

>>> import awswrangler as wr
>>> client = wr.neptune.connect(neptune_endpoint, neptune_port, iam_enabled=False)
>>> wr.neptune.gremlin.to_property_graph(
...     df=df
... )