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feat: ensure Series.str.len() can get length of array columns #497

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Merged
merged 1 commit into from
Mar 22, 2024
Merged

feat: ensure Series.str.len() can get length of array columns #497

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2 changes: 0 additions & 2 deletions 2 tests/system/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -357,8 +357,6 @@ def nested_pandas_df() -> pd.DataFrame:
DATA_DIR / "nested.jsonl",
lines=True,
)
tests.system.utils.convert_pandas_dtypes(df, bytes_col=True)

df = df.set_index("rowindex")
return df

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20 changes: 20 additions & 0 deletions 20 tests/system/small/operations/test_strings.py
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Expand Up @@ -181,6 +181,26 @@ def test_len(scalars_dfs):
)


def test_len_with_array_column(nested_df, nested_pandas_df):
"""
Series.str.len() is expected to work on columns containing lists as well as strings.

See: https://stackoverflow.com/a/41340543/101923
"""
col_name = "event_sequence"
bf_series: bigframes.series.Series = nested_df[col_name]
bf_result = bf_series.str.len().to_pandas()
pd_result = nested_pandas_df[col_name].str.len()

# One of dtype mismatches to be documented. Here, the `bf_result.dtype` is `Int64` but
# the `pd_result.dtype` is `float64`: https://github.com/pandas-dev/pandas/issues/51948
assert_series_equal(
pd_result.astype(pd.Int64Dtype()),
bf_result,
check_index_type=False,
)


def test_lower(scalars_dfs):
scalars_df, scalars_pandas_df = scalars_dfs
col_name = "string_col"
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