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https://issues.apache.org/jira/browse/ARROW-3065?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16626336#comment-16626336
]
David Lee commented on ARROW-3065:
----------------------------------
This test fails.. Tested against 0.10.0.. Works in 0.9.0
{{import pandas as pd}}
{{import pyarrow as pa}}
{{import pyarrow.parquet as pq}}{{schema = pa.schema([}}
{{pa.field('col1', pa.string()),}}
{{pa.field('col2', pa.string()),}}
{{])}}
{{df1 = pd.DataFrame([\{"col1": v, "col2": v} for v in list("abcdefgh")])}}
{{df2 = pd.DataFrame([\{"col2": v} for v in list("abcdefgh")])}}{{df1 =
df1.reindex(columns=schema.names)}}
{{df2 = df2.reindex(columns=schema.names)}}{{tbl1 = pa.Table.from_pandas(df1,
schema = schema, preserve_index=False)}}
{{tbl2 = pa.Table.from_pandas(df2, schema = schema,
preserve_index=False)}}{{tbl3 = pa.concat_tables([tbl1, tbl2])}}{{Traceback
(most recent call last):}}
{{ File "<stdin>", line 1, in <module>}}
{{ File "pyarrow/table.pxi", line 1562, in pyarrow.lib.concat_tables}}
{{ File "pyarrow/error.pxi", line 81, in pyarrow.lib.check_status}}
{{pyarrow.lib.ArrowInvalid: Schema at index 1 was different:}}
> [Python] concat_tables() failing from bad Pandas Metadata
> ---------------------------------------------------------
>
> Key: ARROW-3065
> URL: https://issues.apache.org/jira/browse/ARROW-3065
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.10.0
> Reporter: David Lee
> Priority: Major
> Fix For: 0.12.0
>
>
> Looks like the major bug from
> https://issues.apache.org/jira/browse/ARROW-1941 is back...
> After I downgraded from 0.10.0 to 0.9.0, the error disappeared..
> {code:python}
> new_arrow_table = pa.concat_tables(my_arrow_tables)
> File "pyarrow/table.pxi", line 1562, in pyarrow.lib.concat_tables
> File "pyarrow/error.pxi", line 81, in pyarrow.lib.check_status
> pyarrow.lib.ArrowInvalid: Schema at index 2 was different:
> {code}
> In order to debug this I saved the first 4 arrow tables to 4 parquet files
> and inspected the parquet files. The parquet schema is identical, but the
> Pandas Metadata is different.
> {code:python}
> for i in range(5):
> pq.write_table(my_arrow_tables[i], "test" + str(i) + ".parquet")
> {code}
> It looks like a column which contains empty strings is getting typed as
> float64.
> {code:python}
> >>> test1.schema
> HoldingDetail_Id: string
> metadata
> --------
> {b'pandas': b'{"index_columns": [], "column_indexes": [], "columns": [
> {"name": "HoldingDetail_Id", "field_name": "HoldingDetail_Id", "pandas_type":
> "unicode", "numpy_type": "object", "metadata": null},
> >>> test1[0]
> <Column name='HoldingDetail_Id' type=DataType(string)>
> [
> [
> "Z4",
> "SF",
> "J7",
> "W6",
> "L7",
> "Q9",
> "NE",
> "F7",
> >>> test2.schema
> HoldingDetail_Id: string
> metadata
> --------
> {b'pandas': b'{"index_columns": [], "column_indexes": [], "columns": [
> {"name": "HoldingDetail_Id", "field_name": "HoldingDetail_Id", "pandas_type":
> "unicode", "numpy_type": "float64", "metadata": null},
> >>> test2[0]
> <Column name='HoldingDetail_Id' type=DataType(string)>
> [
> [
> "",
> "",
> "",
> "",
> "",
> "",
> "",
> "",
> {code}
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