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Wes McKinney commented on ARROW-2136: ------------------------------------- We have not yet implemented handling for non-nullable fields in most of the pandas conversions. Probably the simplest thing to do will be to leave the current conversion code as is and then raise an exception if a non-nullable field turns out to have nulls post-conversion to Arrow > Non nullable schema ignored > --------------------------- > > Key: ARROW-2136 > URL: https://issues.apache.org/jira/browse/ARROW-2136 > Project: Apache Arrow > Issue Type: Bug > Components: Python > Affects Versions: 0.8.0 > Reporter: Matthew Gilbert > Priority: Major > > If you provide a schema with {{nullable=False}} but pass a {{DataFrame}} > which in fact has nulls it appears the schema is ignored? I would expect an > error here. > {code} > import pyarrow as pa > import pandas as pd > df = pd.DataFrame({"a":[1.2, 2.1, pd.np.NaN]}) > schema = pa.schema([pa.field("a", pa.float64(), nullable=False)]) > table = pa.Table.from_pandas(df, schema=schema) > table[0] > <pyarrow.lib.Column object at 0x7f213bf2fb70> > chunk 0: <pyarrow.lib.DoubleArray object at 0x7f213bf20ea8> > [ > 1.2, > 2.1, > NA > ] > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005)