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Graph Notebook Version (and Graph Database and Version used if applicable)
4.6.0 (Amazon Neptune 1.2.1.0)
Is your feature request related to a problem? Please describe.
When I use the %%sparql magic with --store-to and --store-format parameters to store the results of a SPARQL SELECT query to a dataframe, all the values in the dataframe are handled as strings, whilst the RDF literals have standard XSD datatypes like xsd:integer or xsd:decimal.
Describe the solution you'd like
When processing the results of a SELECT query, add handling for standard XSD datatypes that can be handled as numerics in a dataframe.
Also add error handling if the lexical value cannot be interpreted according to the datatype. For example a typed literal like "example"^^<http://www.w3.org/2001/XMLSchema#integer> may occur in RDF data, but the value cannot be interpreted as an integer. Could fallback to string in such cases.
Additional context
Workaround is to add a post-processing step to convert values from string to numeric for each variable/field where we expect numeric values:
df.x=pd.to_numeric(df.x, errors='coerce')
The text was updated successfully, but these errors were encountered:
Community Note
Graph Notebook Version (and Graph Database and Version used if applicable)
4.6.0 (Amazon Neptune 1.2.1.0)
Is your feature request related to a problem? Please describe.
When I use the
%%sparql
magic with--store-to
and--store-format
parameters to store the results of a SPARQL SELECT query to a dataframe, all the values in the dataframe are handled as strings, whilst the RDF literals have standard XSD datatypes likexsd:integer
orxsd:decimal
.Describe the solution you'd like
When processing the results of a SELECT query, add handling for standard XSD datatypes that can be handled as numerics in a dataframe.
Also add error handling if the lexical value cannot be interpreted according to the datatype. For example a typed literal like
"example"^^<http://www.w3.org/2001/XMLSchema#integer>
may occur in RDF data, but the value cannot be interpreted as an integer. Could fallback to string in such cases.Additional context
Workaround is to add a post-processing step to convert values from string to numeric for each variable/field where we expect numeric values:
The text was updated successfully, but these errors were encountered: