Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

fix: pyarrow backend trimming timestamp to date #2875

Merged
merged 1 commit into from
Jun 26, 2024
Merged

fix: pyarrow backend trimming timestamp to date #2875

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion awswrangler/_data_types.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -369,7 +369,7 @@ def athena2pandas(dtype: str, dtype_backend: str | None = None) -> str: # noqa:
if (dtype == "string") or dtype.startswith("char") or dtype.startswith("varchar"):
return "string" if dtype_backend != "pyarrow" else "string[pyarrow]"
if dtype in ("timestamp", "timestamp with time zone"):
return "datetime64" if dtype_backend != "pyarrow" else "date64[pyarrow]"
return "datetime64" if dtype_backend != "pyarrow" else "timestamp[ns][pyarrow]"
if dtype == "date":
return "date" if dtype_backend != "pyarrow" else "date32[pyarrow]"
if dtype.startswith("decimal"):
Expand Down
29 changes: 15 additions & 14 deletions tests/_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -334,31 +334,32 @@ def get_df_dtype_backend(dtype_backend: Literal["numpy_nullable", "pyarrow"] = "
"int32_nullable": [1, None, 3],
"int64_nullable": [1, None, 3],
"float_nullable": [0.0, None, 2.2],
# "bool_nullable": [True, None, False],
"bool_nullable": [True, None, False],
"string_nullable": ["Washington", None, "Seattle"],
# "date_nullable": [dt("2020-01-01"), None, dt("2020-01-02")],
# "timestamp_nullable": [ts("2020-01-01 00:00:00.0"), None, ts("2020-01-02 00:00:01.0")],
"date_nullable": [dt("2020-01-01"), None, dt("2020-01-02")],
"timestamp_nullable": [ts("2020-01-01 00:00:00.0"), None, ts("2020-01-02 00:00:01.0")],
}
)
if dtype_backend == "numpy_nullable":
df["int8_nullable"] = df["int8_nullable"].astype("Int8")
df["int16_nullable"] = df["int16_nullable"].astype("Int16")
df["int32_nullable"] = df["int32_nullable"].astype("Int32")
df["int64_nullable"] = df["int64_nullable"].astype("Int64")
df["float_nullable"] = df["float_nullable"].astype("Float64")
# df["bool_nullable"] = df["bool_nullable"].astype("boolean")
# df["date_nullable"] = df["date_nullable"].astype("string[python]")
df["string_nullable"] = df["string_nullable"].astype("string[python]")
df["int8_nullable"] = df["int8_nullable"].astype(pd.Int8Dtype())
df["int16_nullable"] = df["int16_nullable"].astype(pd.Int16Dtype())
df["int32_nullable"] = df["int32_nullable"].astype(pd.Int32Dtype())
df["int64_nullable"] = df["int64_nullable"].astype(pd.Int64Dtype())
df["float_nullable"] = df["float_nullable"].astype(pd.Float64Dtype())
df["bool_nullable"] = df["bool_nullable"].astype(pd.BooleanDtype())
df["string_nullable"] = df["string_nullable"].astype(pd.StringDtype())
df["timestamp_nullable"] = df["timestamp_nullable"].astype(pd.DatetimeTZDtype())
df["date_nullable"] = df["date_nullable"].astype(pd.StringDtype())
elif dtype_backend == "pyarrow":
df["int8_nullable"] = df["int8_nullable"].astype(pd.ArrowDtype(pa.int8()))
df["int16_nullable"] = df["int16_nullable"].astype(pd.ArrowDtype(pa.int16()))
df["int32_nullable"] = df["int32_nullable"].astype(pd.ArrowDtype(pa.int32()))
df["int64_nullable"] = df["int64_nullable"].astype(pd.ArrowDtype(pa.int64()))
df["float_nullable"] = df["float_nullable"].astype(pd.ArrowDtype(pa.float64()))
# df["bool_nullable"] = df["bool_nullable"].astype(pd.ArrowDtype(pa.bool_()))
# df["date_nullable"] = df["date_nullable"].astype(pd.ArrowDtype(pa.string()))
df["bool_nullable"] = df["bool_nullable"].astype(pd.ArrowDtype(pa.bool_()))
df["string_nullable"] = df["string_nullable"].astype(pd.ArrowDtype(pa.string()))
# df["timestamp_nullable"] = df["timestamp_nullable"].astype("date64[ms][pyarrow]")
df["date_nullable"] = df["date_nullable"].astype(pd.ArrowDtype(pa.date32()))
df["timestamp_nullable"] = df["timestamp_nullable"].astype(pd.ArrowDtype(pa.timestamp("ns")))
else:
raise ValueError(f"Unknown dtype_backend: {dtype_backend}")
return df
Expand Down
2 changes: 1 addition & 1 deletion tests/unit/test_pandas_pyarrow_dtype_backend.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -105,7 +105,7 @@ def test_athena_csv_dtype_backend(
df["string_nullable"] = df["string_nullable"].astype("string[pyarrow]")

if ctas_approach or unload_approach:
df2["string_nullable"].replace("", pa.NA, inplace=True)
df2["string_nullable"] = df2["string_nullable"].replace("", pa.NA)

assert_pandas_equals(df, df2)

Expand Down
Loading