remove standardd community imports boilerplate

Author: tswast

bigframes/bigquery/_operations/array.py

@@ -77,7 +77,6 @@ def array_agg(
 
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
-        >>> import numpy as np
 
     For a SeriesGroupBy object:
 
@@ -126,7 +125,6 @@ def array_to_string(series: series.Series, delimiter: str) -> series.Series:
 
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
-        >>> import numpy as np
 
         >>> s = bpd.Series([["H", "i", "!"], ["Hello", "World"], np.nan, [], ["Hi"]])
         >>> bbq.array_to_string(s, delimiter=", ")

bigframes/bigquery/_operations/datetime.py

@@ -21,7 +21,6 @@ def unix_seconds(input: series.Series) -> series.Series:
 
     **Examples:**
 
-        >>> import pandas as pd
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
 
@@ -47,7 +46,6 @@ def unix_millis(input: series.Series) -> series.Series:
 
     **Examples:**
 
-        >>> import pandas as pd
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
 
@@ -73,7 +71,6 @@ def unix_micros(input: series.Series) -> series.Series:
 
     **Examples:**
 
-        >>> import pandas as pd
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
 

bigframes/bigquery/_operations/json.py

@@ -49,7 +49,6 @@ def json_set(
 
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
-        >>> import numpy as np
 
         >>> s = bpd.read_gbq("SELECT JSON '{\\\"a\\\": 1}' AS data")["data"]
         >>> bbq.json_set(s, json_path_value_pairs=[("$.a", 100), ("$.b", "hi")])

bigframes/bigquery/_operations/sql.py

@@ -36,8 +36,6 @@ def sql_scalar(
 
         >>> import bigframes.pandas as bpd
         >>> import bigframes.bigquery as bbq
-        >>> import pandas as pd
-        >>> import pyarrow as pa
 
         >>> s = bpd.Series(["1.5", "2.5", "3.5"])
         >>> s = s.astype(pd.ArrowDtype(pa.decimal128(38, 9)))

bigframes/dataframe.py

@@ -4250,7 +4250,6 @@ def _resample(
         **Examples:**
 
         >>> import bigframes.pandas as bpd
-        >>> import pandas as pd
 
         >>> data = {
         ...     "timestamp_col": pd.date_range(

bigframes/series.py

@@ -2419,7 +2419,6 @@ def _resample(
         **Examples:**
 
         >>> import bigframes.pandas as bpd
-        >>> import pandas as pd
 
         >>> data = {
         ...     "timestamp_col": pd.date_range(

bigframes/session/__init__.py

@@ -948,7 +948,6 @@ def read_pandas(
         **Examples:**
 
             >>> import bigframes.pandas as bpd
-            >>> import pandas as pd
 
             >>> d = {'col1': [1, 2], 'col2': [3, 4]}
             >>> pandas_df = pd.DataFrame(data=d)
@@ -2078,7 +2077,6 @@ def read_gbq_function(
         note, row processor implies that the function has only one input
         parameter.
 
-            >>> import pandas as pd
             >>> @bpd.remote_function(cloud_function_service_account="default")
             ... def row_sum(s: pd.Series) -> float:
             ...     return s['a'] + s['b'] + s['c']

third_party/bigframes_vendored/ibis/expr/api.py

@@ -1532,7 +1532,6 @@ def read_parquet(
     Examples
     --------
     >>> import ibis
-    >>> import pandas as pd
     >>> ibis.options.interactive = True
     >>> df = pd.DataFrame({"a": [1, 2, 3], "b": list("ghi")})
     >>> df
@@ -1582,7 +1581,6 @@ def read_delta(
     Examples
     --------
     >>> import ibis
-    >>> import pandas as pd
     >>> ibis.options.interactive = True
     >>> df = pd.DataFrame({"a": [1, 2, 3], "b": list("ghi")})
     >>> df

third_party/bigframes_vendored/ibis/expr/datatypes/core.py

@@ -62,7 +62,6 @@ def dtype(value: Any, nullable: bool = True) -> DataType:
 
     Or other type systems, like numpy/pandas/pyarrow types:
 
-    >>> import pyarrow as pa
     >>> ibis.dtype(pa.int32())
     Int32(nullable=True)
 

third_party/bigframes_vendored/ibis/expr/types/arrays.py

@@ -1008,7 +1008,6 @@ def flatten(self) -> ir.ArrayValue:
         ...     "nulls_only": [None, None, None],
         ...     "mixed_nulls": [[], None, [None]],
         ... }
-        >>> import pyarrow as pa
         >>> t = ibis.memtable(
         ...     pa.Table.from_pydict(
         ...         data,