googleapis
diff --git a/‎third_party/bigframes_vendored/pandas/core/frame.py‎
Lines changed: 165 additions & 14 deletions b/‎third_party/bigframes_vendored/pandas/core/frame.py‎
Lines changed: 165 additions & 14 deletions
@@ -3414,18 +3414,75 @@ def melt(self, id_vars, value_vars, var_name, value_name):
  the row axis, leaving just two non-identifier columns, 'variable' and
  'value'.
 
- Parameters
- ----------
- id_vars (tuple, list, or ndarray, optional):
- Column(s) to use as identifier variables.
- value_vars (tuple, list, or ndarray, optional):
- Column(s) to unpivot. If not specified, uses all columns that
- are not set as `id_vars`.
- var_name (scalar):
- Name to use for the 'variable' column. If None it uses
- ``frame.columns.name`` or 'variable'.
- value_name (scalar, default 'value'):
- Name to use for the 'value' column.
+ **Examples:**
+
+ >>> import bigframes.pandas as bpd
+ >>> bpd.options.display.progress_bar = None
+
+ >>> df = bpd.DataFrame({"A": [1, None, 3, 4, 5],
+ ... "B": [1, 2, 3, 4, 5],
+ ... "C": [None, 3.5, None, 4.5, 5.0]})
+ >>> df
+ A B C
+ 0 1.0 1	<NA>
+ 1 <NA> 2 3.5
+ 2 3.0 3	<NA>
+ 3 4.0 4 4.5
+ 4 5.0 5 5.0
+ <BLANKLINE>
+ [5 rows x 3 columns]
+
+ Using `melt` without optional arguments:
+
+ >>> df.melt()
+ variable value
+ 0 A 1.0
+ 1 A <NA>
+ 2 A 3.0
+ 3 A 4.0
+ 4 A 5.0
+ 5 B 1.0
+ 6 B 2.0
+ 7 B 3.0
+ 8 B 4.0
+ 9 B 5.0
+ 10 C <NA>
+ 11 C 3.5
+ 12 C <NA>
+ 13 C 4.5
+ 14 C 5.0
+ <BLANKLINE>
+ [15 rows x 2 columns]
+
+ Using `melt` with `id_vars` and `value_vars`:
+
+ >>> df.melt(id_vars='A', value_vars=['B', 'C'])
+ A	variable	value
+ 0 1.0 B 1
+ 1	<NA> B 2
+ 2 3.0 B 3
+ 3 4.0 B 4
+ 4 5.0 B 5
+ 5 1.0 C <NA>
+ 6 <NA> C 3
+ 7 3.0 C <NA>
+ 8 4.0 C 4
+ 9 5.0 C 5
+ <BLANKLINE>
+ [10 rows x 3 columns]
+
+
+ Args:
+ id_vars (tuple, list, or ndarray, optional):
+ Column(s) to use as identifier variables.
+ value_vars (tuple, list, or ndarray, optional):
+ Column(s) to unpivot. If not specified, uses all columns that
+ are not set as `id_vars`.
+ var_name (scalar):
+ Name to use for the 'variable' column. If None it uses
+ ``frame.columns.name`` or 'variable'.
+ value_name (scalar, default 'value'):
+ Name to use for the 'value' column.
 
  Returns:
  DataFrame: Unpivoted DataFrame.
@@ -3757,6 +3814,52 @@ def pivot(self, *, columns, index=None, values=None):
  do not together uniquely identify input rows, the output will be
  silently non-deterministic.
 
+ **Examples:**
+
+ >>> import bigframes.pandas as bpd
+ >>> bpd.options.display.progress_bar = None
+
+ >>> df = bpd.DataFrame({
+ ... "foo": ["one", "one", "one", "two", "two"],
+ ... "bar": ["A", "B", "C", "A", "B"],
+ ... "baz": [1, 2, 3, 4, 5],
+ ... "zoo": ['x', 'y', 'z', 'q', 'w']
+ ... })
+
+ >>> df
+ foo	bar	baz	zoo
+ 0	one A 1 x
+ 1	one B 2 y
+ 2	one C 3 z
+ 3	two A 4 q
+ 4	two B 5 w
+ <BLANKLINE>
+ [5 rows x 4 columns]
+
+ Using `pivot` without optional arguments:
+
+ >>> df.pivot(columns='foo')
+ bar baz zoo
+ foo one two one two one two
+ 0 A	<NA> 1	<NA> x	<NA>
+ 1 B	<NA> 2	<NA> y	<NA>
+ 2 C	<NA> 3	<NA> z	<NA>
+ 3	<NA> A	<NA> 4	<NA> q
+ 4	<NA> B	<NA> 5	<NA> w
+ <BLANKLINE>
+ [5 rows x 6 columns]
+
+ Using `pivot` with `index` and `values`:
+
+ >>> df.pivot(columns='foo', index='bar', values='baz')
+ foo one two
+ bar
+ A 1 4
+ B 2 5
+ C 3 <NA>
+ <BLANKLINE>
+ [3 rows x 2 columns]
+
  Args:
  columns (str or object or a list of str):
  Column to use to make new frame's columns.
@@ -3774,7 +3877,7 @@ def pivot(self, *, columns, index=None, values=None):
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
- def stack(self):
+ def stack(self, level=-1):
  """
  Stack the prescribed level(s) from columns to index.
 
@@ -3792,12 +3895,36 @@ def stack(self):
  BigQuery DataFrames does not support stack operations that would
  combine columns of different dtypes.
 
+ **Example:**
+
+ >>> import bigframes.pandas as bpd
+ >>> bpd.options.display.progress_bar = None
+
+ >>> df = bpd.DataFrame({'A': [1, 3], 'B': [2, 4]}, index=['foo', 'bar'])
+ >>> df
+ A	B
+ foo 1	2
+ bar 3	4
+ <BLANKLINE>
+ [2 rows x 2 columns]
+
+ >>> df.stack()
+ foo A 1
+ B 2
+ bar A 3
+ B 4
+ dtype: Int64
+
+ Args:
+ level (int, str, or list of these, default -1 (last level)):
+ Level(s) to stack from the column axis onto the index axis.
+
  Returns:
  DataFrame or Series: Stacked dataframe or series.
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
- def unstack(self):
+ def unstack(self, level=-1):
  """
  Pivot a level of the (necessarily hierarchical) index labels.
 
@@ -3807,6 +3934,30 @@ def unstack(self):
  If the index is not a MultiIndex, the output will be a Series
  (the analogue of stack when the columns are not a MultiIndex).
 
+ **Example:**
+
+ >>> import bigframes.pandas as bpd
+ >>> bpd.options.display.progress_bar = None
+
+ >>> df = bpd.DataFrame({'A': [1, 3], 'B': [2, 4]}, index=['foo', 'bar'])
+ >>> df
+ A	B
+ foo 1	2
+ bar 3	4
+ <BLANKLINE>
+ [2 rows x 2 columns]
+
+ >>> df.unstack()
+ A foo 1
+ bar 3
+ B foo 2
+ bar 4
+ dtype: Int64
+
+ Args:
+ level (int, str, or list of these, default -1 (last level)):
+ Level(s) of index to unstack, can pass level name.
+
  Returns:
  DataFrame or Series: DataFrame or Series.
  """