@@ -304,6 +304,9 @@ def __len__(self):
 rows, _ = self.shape
 return rows
 
+def __iter__(self):
+return iter(self.columns)
+
 def astype(
 self,
 dtype: Union[bigframes.dtypes.DtypeString, bigframes.dtypes.Dtype],
@@ -1477,12 +1480,27 @@ def isin(self, values) -> DataFrame:
 f"isin(), you passed a [{type(values).__name__}]"
 )
 
+def keys(self) -> pandas.Index:
+return self.columns
+
 def items(self):
 column_ids = self._block.value_columns
 column_labels = self._block.column_labels
 for col_id, col_label in zip(column_ids, column_labels):
 yield col_label, bigframes.series.Series(self._block.select_column(col_id))
 
+def iterrows(self) -> Iterable[tuple[typing.Any, pandas.Series]]:
+for df in self.to_pandas_batches():
+for item in df.iterrows():
+yield item
+
+def itertuples(
+self, index: bool = True, name: typing.Optional[str] = "Pandas"
+) -> Iterable[tuple[typing.Any, ...]]:
+for df in self.to_pandas_batches():
+for item in df.itertuples(index=index, name=name):
+yield item
+
 def dropna(
 self,
 *,

@@ -16,6 +16,7 @@
 
 from __future__ import annotations
 
+import itertools
 import numbers
 import textwrap
 import typing
@@ -148,6 +149,11 @@ def _set_internal_query_job(self, query_job: bigquery.QueryJob):
 def __len__(self):
 return self.shape[0]
 
+def __iter__(self) -> typing.Iterator:
+return itertools.chain.from_iterable(
+map(lambda x: x.index, self._block.to_pandas_batches())
+)
+
 def copy(self) -> Series:
 return Series(self._block)
 

@@ -803,6 +803,55 @@ def test_apply_series_scalar_callable(
 pandas.testing.assert_series_equal(bf_result, pd_result)
 
 
+def test_df_keys(
+scalars_df_index,
+scalars_pandas_df_index,
+):
+pandas.testing.assert_index_equal(
+scalars_df_index.keys(), scalars_pandas_df_index.keys()
+)
+
+
+def test_df_iter(
+scalars_df_index,
+scalars_pandas_df_index,
+):
+for bf_i, df_i in zip(scalars_df_index, scalars_pandas_df_index):
+assert bf_i == df_i
+
+
+def test_iterrows(
+scalars_df_index,
+scalars_pandas_df_index,
+):
+for (bf_index, bf_series), (pd_index, pd_series) in zip(
+scalars_df_index.iterrows(), scalars_pandas_df_index.iterrows()
+):
+assert bf_index == pd_index
+pandas.testing.assert_series_equal(bf_series, pd_series)
+
+
+@pytest.mark.parametrize(
+(
+"index",
+"name",
+),
+[
+(
+True,
+"my_df",
+),
+(False, None),
+],
+)
+def test_itertuples(scalars_df_index, index, name):
+# Numeric has slightly different representation as a result of conversions.
+bf_tuples = scalars_df_index.itertuples(index, name)
+pd_tuples = scalars_df_index.to_pandas().itertuples(index, name)
+for bf_tuple, pd_tuple in zip(bf_tuples, pd_tuples):
+assert bf_tuple == pd_tuple
+
+
 def test_df_isin_list(scalars_dfs):
 scalars_df, scalars_pandas_df = scalars_dfs
 values = ["Hello, World!", 55555, 2.51, pd.NA, True]

@@ -975,6 +975,85 @@ def isin(self, values):
 """
 raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+def keys(self):
+"""
+Get the 'info axis'.
+
+This is index for Series, columns for DataFrame.
+
+Returns:
+Index: Info axis.
+
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> df = bpd.DataFrame({
+... 'A': [1, 2, 3],
+... 'B': [4, 5, 6],
+... })
+>>> df.keys()
+Index(['A', 'B'], dtype='object')
+"""
+raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
+def iterrows(self):
+"""
+Iterate over DataFrame rows as (index, Series) pairs.
+
+Yields:
+a tuple (index, data) where data contains row values as a Series
+
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+>>> df = bpd.DataFrame({
+... 'A': [1, 2, 3],
+... 'B': [4, 5, 6],
+... })
+>>> index, row = next(df.iterrows())
+>>> index
+0
+>>> row
+A 1
+B 4
+Name: 0, dtype: object
+"""
+raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
+def itertuples(self, index: bool = True, name: str | None = "Pandas"):
+"""
+Iterate over DataFrame rows as namedtuples.
+
+Args:
+index (bool, default True):
+If True, return the index as the first element of the tuple.
+name (str or None, default "Pandas"):
+The name of the returned namedtuples or None to return regular
+tuples.
+
+Returns:
+iterator:
+An object to iterate over namedtuples for each row in the
+DataFrame with the first field possibly being the index and
+following fields being the column values.
+
+
+**Examples:**
+
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+>>> df = bpd.DataFrame({
+... 'A': [1, 2, 3],
+... 'B': [4, 5, 6],
+... })
+>>> next(df.itertuples(name="Pair"))
+Pair(Index=0, A=1, B=4)
+"""
+raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
 def items(self):
 """
 Iterate over (column name, Series) pairs.

@@ -1,7 +1,7 @@
 # Contains code from https://.com/pandas-dev/pandas/blob/main/pandas/core/generic.py
 from __future__ import annotations
 
-from typing import Literal, Optional
+from typing import Iterator, Literal, Optional
 
 from bigframes import constants
 from third_party.bigframes_vendored.pandas.core import indexing
@@ -35,6 +35,35 @@ def size(self) -> int:
 """
 raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+def __iter__(self) -> Iterator:
+"""
+Iterate over info axis.
+
+Returns
+iterator: Info axis as iterator.
+
+**Examples:**
+>>> import bigframes.pandas as bpd
+>>> bpd.options.display.progress_bar = None
+
+>>> df = bpd.DataFrame({
+... 'A': [1, 2, 3],
+... 'B': [4, 5, 6],
+... })
+>>> for x in df:
+... print(x)
+A
+B
+
+>>> series = bpd.Series(["a", "b", "c"], index=[10, 20, 30])
+>>> for x in series:
+... print(x)
+10
+20
+30
+"""
+raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
 # -------------------------------------------------------------------------
 # Unary Methods