remove bpd boilerplate

Author: tswast

bigframes/dataframe.py

@@ -1770,7 +1770,6 @@ def to_pandas(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
             >>> df = bpd.DataFrame({'col': [4, 2, 2]})
 
         Download the data from BigQuery and convert it into an in-memory pandas DataFrame.
@@ -1891,7 +1890,6 @@ def to_pandas_batches(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
             >>> df = bpd.DataFrame({'col': [4, 3, 2, 2, 3]})
 
         Iterate through the results in batches, limiting the total rows yielded
@@ -4249,7 +4247,6 @@ def _resample(
 
         **Examples:**
 
-        >>> import bigframes.pandas as bpd
 
         >>> data = {
         ...     "timestamp_col": pd.date_range(

bigframes/operations/strings.py

@@ -67,7 +67,6 @@ def reverse(self) -> series.Series:
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
             >>> s = bpd.Series(["apple", "banana", "", bpd.NA])
             >>> s.str.reverse()

bigframes/series.py

@@ -532,7 +532,6 @@ def to_pandas(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
             >>> s = bpd.Series([4, 3, 2])
 
         Download the data from BigQuery and convert it into an in-memory pandas Series.
@@ -659,7 +658,6 @@ def to_pandas_batches(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
             >>> s = bpd.Series([4, 3, 2, 2, 3])
 
         Iterate through the results in batches, limiting the total rows yielded
@@ -2418,7 +2416,6 @@ def _resample(
 
         **Examples:**
 
-        >>> import bigframes.pandas as bpd
 
         >>> data = {
         ...     "timestamp_col": pd.date_range(

bigframes/session/__init__.py

@@ -617,7 +617,6 @@ def read_gbq_query(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
         Simple query input:
 
@@ -772,7 +771,6 @@ def read_gbq_table(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
         Read a whole table, with arbitrary ordering or ordering corresponding to the primary key(s).
 
@@ -850,7 +848,6 @@ def read_gbq_table_streaming(
         **Examples:**
 
             >>> import bigframes.streaming as bst
-            >>> import bigframes.pandas as bpd
 
             >>> sdf = bst.read_gbq_table("bigquery-public-data.ml_datasets.penguins")
 
@@ -878,7 +875,6 @@ def read_gbq_model(self, model_name: str):
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
         Read an existing BigQuery ML model.
 
@@ -947,7 +943,6 @@ def read_pandas(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
             >>> d = {'col1': [1, 2], 'col2': [3, 4]}
             >>> pandas_df = pd.DataFrame(data=d)
@@ -1823,7 +1818,6 @@ def udf(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
             >>> import datetime
 
         Turning an arbitrary python function into a BigQuery managed python udf:
@@ -1986,7 +1980,6 @@ def read_gbq_function(
 
         **Examples:**
 
-            >>> import bigframes.pandas as bpd
 
         Use the [cw_lower_case_ascii_only](https://github.com/GoogleCloudPlatform/bigquery-utils/blob/master/udfs/community/README.md#cw_lower_case_ascii_onlystr-string)
         function from Community UDFs.

third_party/bigframes_vendored/pandas/core/computation/eval.py

@@ -172,7 +172,6 @@ def eval(
 
     **Examples:**
 
-        >>> import bigframes.pandas as bpd
 
         >>> df = bpd.DataFrame({"animal": ["dog", "pig"], "age": [10, 20]})
         >>> df

third_party/bigframes_vendored/pandas/core/config_init.py

@@ -19,7 +19,6 @@
 
 Define Repr mode to "deferred" will prevent job execution in repr.
 
-    >>> import bigframes.pandas as bpd
     >>> df = bpd.read_gbq("bigquery-public-data.ml_datasets.penguins")
 
     >>> bpd.options.display.repr_mode = "deferred"