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fix: handle None when converting numerics to parquet #768

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merged 7 commits into from
May 29, 2024
Merged

fix: handle None when converting numerics to parquet #768

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a87a00d
fix: handle None when converting numerics to parquet
Linchin May 13, 2024
89ad977
lint and fix unit test
Linchin May 13, 2024
11ef479
Merge branch 'main' into null-nums
Linchin May 13, 2024
9fbd41c
add check for pandas.NA
Linchin May 20, 2024
7c64619
Merge branch 'main' into null-nums
Linchin May 20, 2024
483195c
Merge branch 'main' into null-nums
Linchin May 21, 2024
46c1842
Merge branch 'main' into null-nums
Linchin May 28, 2024
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10 changes: 9 additions & 1 deletion pandas_gbq/load.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,15 @@ def cast_dataframe_for_parquet(
errors="ignore",
)
elif column_type in {"NUMERIC", "DECIMAL", "BIGNUMERIC", "BIGDECIMAL"}:
cast_column = dataframe[column_name].map(decimal.Decimal)
# decimal.Decimal does not support `None` input, add support here.
# https://github.com/googleapis/python-bigquery-pandas/issues/719
def convert(x):
if x is None:
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@chalmerlowe chalmerlowe May 15, 2024 •
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QUESTION:

The original issue mentions that None and pd.NA are not handled appropriately.

This code seems to only address None.
Is the intent to check for both?

IF yes... this may be a possible check that is more general AND as other edge cases arise could enable edits to the code quickly and easily.

Suggested change
if x is None:
if x in {None, pd.NA}:

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Indeed, thank you for catching this! I'll update the code.

return decimal.Decimal("NaN")
else:
return decimal.Decimal(x)

cast_column = dataframe[column_name].map(convert)
else:
cast_column = None

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21 changes: 21 additions & 0 deletions tests/unit/test_load.py
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Expand Up @@ -370,3 +370,24 @@ def test_cast_dataframe_for_parquet_w_null_fields():
schema = {"fields": None}
result = load.cast_dataframe_for_parquet(dataframe, schema)
pandas.testing.assert_frame_equal(result, expected)


# Verifies null numerics are properly handled
# https://github.com/googleapis/python-bigquery-pandas/issues/719
def test_cast_dataframe_for_parquet_w_null_numerics():
from decimal import Decimal

dataframe = pandas.DataFrame(
{
"A": pandas.Series([Decimal("5413.36"), Decimal("nan"), None]),
},
)

schema = {"fields": [{"name": "A", "type": "BIGNUMERIC"}]}
result = load.cast_dataframe_for_parquet(dataframe, schema)

# pandas.testing.assert_frame_equal() doesn't distinguish Decimal('nan')
# vs. None, verify Decimal("nan") directly.
# https://github.com/pandas-dev/pandas/issues/18463
assert result["A"][1].is_nan()
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assert result["A"][2].is_nan()