@@ -342,6 +342,51 @@ def read_gbq_query(
 ``row_number() over ()`` if there is no natural unique index or you
 want to preserve ordering.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+Simple query input:
+
+>>> df = bpd.read_gbq_query('''
+... SELECT
+... pitcherFirstName,
+... pitcherLastName,
+... pitchSpeed,
+... FROM `bigquery-public-data.baseball.games_wide`
+... ''')
+>>> df.head(2)
+pitcherFirstName pitcherLastName pitchSpeed
+0 0
+1 0
+<BLANKLINE>
+[2 rows x 3 columns]
+
+Preserve ordering in a query input.
+
+>>> df = bpd.read_gbq_query('''
+... SELECT
+... -- Instead of an ORDER BY clause on the query, use
+... -- ROW_NUMBER() to create an ordered DataFrame.
+... ROW_NUMBER() OVER (ORDER BY AVG(pitchSpeed) DESC)
+... AS rowindex,
+...
+... pitcherFirstName,
+... pitcherLastName,
+... AVG(pitchSpeed) AS averagePitchSpeed
+... FROM `bigquery-public-data.baseball.games_wide`
+... WHERE year = 2016
+... GROUP BY pitcherFirstName, pitcherLastName
+... ''', index_col="rowindex")
+>>> df.head(2)
+pitcherFirstName pitcherLastName averagePitchSpeed
+rowindex
+1 Albertin Chapman 96.514113
+2 Zachary Britton 94.591039
+<BLANKLINE>
+[2 rows x 3 columns]
+
 See also: :meth:`Session.read_gbq`.
 """
 # NOTE: This method doesn't (yet) exist in pandas or pandas-gbq, so
@@ -405,6 +450,25 @@ def read_gbq_table(
 ) -> dataframe.DataFrame:
 """Turn a BigQuery table into a DataFrame.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+Read a whole table, with arbitrary ordering or ordering corresponding to the primary key(s).
+
+>>> df = bpd.read_gbq_table("bigquery-public-data.ml_datasets.penguins")
+>>> df.head(2)
+species island culmen_length_mm \\
+0 Adelie Penguin (Pygoscelis adeliae) Dream 36.6
+1 Adelie Penguin (Pygoscelis adeliae) Dream 39.8
+<BLANKLINE>
+culmen_depth_mm flipper_length_mm body_mass_g sex
+0 18.4 184.0 3475.0 FEMALE
+1 19.1 184.0 4650.0 MALE
+<BLANKLINE>
+[2 rows x 7 columns]
+
 See also: :meth:`Session.read_gbq`.
 """
 # NOTE: This method doesn't (yet) exist in pandas or pandas-gbq, so
@@ -792,6 +856,16 @@ def _read_ibis(
 def read_gbq_model(self, model_name: str):
 """Loads a BigQuery ML model from BigQuery.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+Read an existing BigQuery ML model.
+
+>>> model_name = "bigframes-dev.bqml_tutorial.penguins_model"
+>>> model = bpd.read_gbq_model(model_name)
+
 Args:
 model_name (str):
 the model's name in BigQuery in the format
@@ -815,6 +889,22 @@ def read_pandas(self, pandas_dataframe: pandas.DataFrame) -> dataframe.DataFrame
 The pandas DataFrame will be persisted as a temporary BigQuery table, which can be
 automatically recycled after the Session is closed.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> import pandas as pd
+>>> bpd.options.display.progress_bar = None
+
+>>> d = {'col1': [1, 2], 'col2': [3, 4]}
+>>> pandas_df = pd.DataFrame(data=d)
+>>> df = bpd.read_pandas(pandas_df)
+>>> df
+col1 col2
+0 1 3
+1 2 4
+<BLANKLINE>
+[2 rows x 2 columns]
+
 Args:
 pandas_dataframe (pandas.DataFrame):
 a pandas DataFrame object to be loaded.
@@ -1365,6 +1455,16 @@ def read_gbq_function(
 The return type of the function must be explicitly specified in the
 function's original definition even if not otherwise required.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> function_name = "bqutil.fn.cw_lower_case_ascii_only"
+>>> func = bpd.read_gbq_function(function_name=function_name)
+>>> func.bigframes_remote_function
+'bqutil.fn.cw_lower_case_ascii_only'
+
 Args:
 function_name (str):
 the function's name in BigQuery in the format

@@ -42,9 +42,23 @@ def read_gbq(
 >>> import bigframes.pandas as bpd
 >>> bpd.options.display.progress_bar = None
 
+If the input is a table ID:
+
+>>> df = bpd.read_gbq("bigquery-public-data.ml_datasets.penguins")
+>>> df.head(2)
+species island culmen_length_mm \\
+0 Adelie Penguin (Pygoscelis adeliae) Dream 36.6
+1 Adelie Penguin (Pygoscelis adeliae) Dream 39.8
+<BLANKLINE>
+culmen_depth_mm flipper_length_mm body_mass_g sex
+0 18.4 184.0 3475.0 FEMALE
+1 19.1 184.0 4650.0 MALE
+<BLANKLINE>
+[2 rows x 7 columns]
+
 Preserve ordering in a query input.
 
->>> bpd.read_gbq('''
+>>> df = bpd.read_gbq('''
 ... SELECT
 ... -- Instead of an ORDER BY clause on the query, use
 ... -- ROW_NUMBER() to create an ordered DataFrame.
@@ -57,16 +71,14 @@ def read_gbq(
 ... FROM `bigquery-public-data.baseball.games_wide`
 ... WHERE year = 2016
 ... GROUP BY pitcherFirstName, pitcherLastName
-... ''', index_col="rowindex").head(n=5)
+... ''', index_col="rowindex")
+>>> df.head(2)
 pitcherFirstName pitcherLastName averagePitchSpeed
 rowindex
 1 Albertin Chapman 96.514113
 2 Zachary Britton 94.591039
-3 Trevor Rosenthal 94.213953
-4 Jose Torres 94.103448
-5 Tayron Guerrero 93.863636
 <BLANKLINE>
-[5 rows x 3 columns]
+[2 rows x 3 columns]
 
 Args:
 query_or_table (str):

@@ -17,6 +17,20 @@ def read_parquet(
 Instead, set a serialized index column as the index and sort by
 that in the resulting DataFrame.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> gcs_path = "gs://cloud-samples-data/bigquery/us-states/us-states.parquet"
+>>> df = bpd.read_parquet(path=gcs_path)
+>>> df.head(2)
+name post_abbr
+0 Alabama AL
+1 Alaska AK
+<BLANKLINE>
+[2 rows x 2 columns]
+
 Args:
 path (str):
 Local or Cloud Storage path to Parquet file.

@@ -55,6 +55,20 @@ def read_csv(
 file. Instead, set a serialized index column as the index and sort by
 that in the resulting DataFrame.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> gcs_path = "gs://cloud-samples-data/bigquery/us-states/us-states.csv"
+>>> df = bpd.read_csv(filepath_or_buffer=gcs_path)
+>>> df.head(2)
+name post_abbr
+0 Alabama AL
+1 Alaska AK
+<BLANKLINE>
+[2 rows x 2 columns]
+
 Args:
 filepath_or_buffer (str):
 A local or Google Cloud Storage (`gs://`) path with `engine="bigquery"`
@@ -64,7 +78,7 @@ def read_csv(
 can be any ISO-8859-1 single-byte character. To use a character in the range
 128-255, you must encode the character as UTF-8. Both engines support
 `sep="\t"` to specify tab character as separator. Default engine supports
-having any number of spaces as separator by specifying `sep="\s+"`. Separators
+having any number of spaces as separator by specifying `sep="\\s+"`. Separators
 longer than 1 character are interpreted as regular expressions by the default
 engine. BigQuery engine only supports single character separators.
 header (Optional[int], default 0):
@@ -146,6 +160,20 @@ def read_json(
 file. Instead, set a serialized index column as the index and sort by
 that in the resulting DataFrame.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> gcs_path = "gs://bigframes-dev-testing/sample1.json"
+>>> df = bpd.read_json(path_or_buf=gcs_path, lines=True, orient="records")
+>>> df.head(2)
+id name
+0 1 Alice
+1 2 Bob
+<BLANKLINE>
+[2 rows x 2 columns]
+
 Args:
 path_or_buf (a valid JSON str, path object or file-like object):
 A local or Google Cloud Storage (`gs://`) path with `engine="bigquery"`

@@ -25,6 +25,24 @@ def read_pickle(
 If the content of the pickle file is a Series and its name attribute is None,
 the name will be set to '0' by default.
 
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> gcs_path = "gs://bigframes-dev-testing/test_pickle.pkl"
+>>> df = bpd.read_pickle(filepath_or_buffer=gcs_path)
+>>> df.head(2)
+species island culmen_length_mm \\
+0 Adelie Penguin (Pygoscelis adeliae) Dream 36.6
+1 Adelie Penguin (Pygoscelis adeliae) Dream 39.8
+<BLANKLINE>
+culmen_depth_mm flipper_length_mm body_mass_g sex
+0 18.4 184.0 3475.0 FEMALE
+1 19.1 184.0 4650.0 MALE
+<BLANKLINE>
+[2 rows x 7 columns]
+
 Args:
 filepath_or_buffer (str, path object, or file-like object):
 String, path object (implementing os.PathLike[str]), or file-like object