fix docstring

Author: chelsea-lin

bigframes/operations/plotting.py

@@ -42,7 +42,7 @@ def line(
  **kwargs,
  ):
  return bfplt.plot(
- self._parent,
+ self._parent.copy(),
  kind="line",
  x=x,
  y=y,

third_party/bigframes_vendored/pandas/plotting/_core.py

@@ -19,24 +19,7 @@ def hist(
  into bins and draws all bins in one :class:`matplotlib.axes.Axes`.
  This is useful when the DataFrame's Series are in a similar scale.
 
- Parameters
- ----------
- by : str or sequence, optional
- Column in the DataFrame to group by. It is not supported yet.
- bins : int, default 10
- Number of histogram bins to be used.
- **kwargs
- Additional keyword arguments are documented in
- :meth:`DataFrame.plot`.
-
- Returns
- -------
- class:`matplotlib.AxesSubplot`
- Return a histogram plot.
-
- Examples
- --------
- For Series:
+ **Examples:**
 
  .. plot::
  :context: close-figs
@@ -46,6 +29,19 @@ def hist(
  >>> df = bpd.DataFrame(np.random.randint(1, 7, 6000), columns=['one'])
  >>> df['two'] = np.random.randint(1, 7, 6000) + np.random.randint(1, 7, 6000)
  >>> ax = df.plot.hist(bins=12, alpha=0.5)
+
+ Args:
+ by (str or sequence, optional):
+ Column in the DataFrame to group by. It is not supported yet.
+ bins (int, default 10):
+ Number of histogram bins to be used.
+ **kwargs:
+ Additional keyword arguments are documented in
+ :meth:`DataFrame.plot`.
+
+ Returns:
+ class:`matplotlib.AxesSubplot`: A histogram plot.
+
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
@@ -63,48 +59,7 @@ def line(
  of items. For consistent results, the random sampling is reproducible.
  Use the `sampling_random_state` parameter to modify the sampling seed.
 
- Parameters
- ----------
- x : label or position, optional
- Allows plotting of one column versus another. If not specified,
- the index of the DataFrame is used.
- y : label or position, optional
- Allows plotting of one column versus another. If not specified,
- all numerical columns are used.
- color : str, array-like, or dict, optional
- The color for each of the DataFrame's columns. Possible values are:
-
- - A single color string referred to by name, RGB or RGBA code,
- for instance 'red' or '#a98d19'.
-
- - A sequence of color strings referred to by name, RGB or RGBA
- code, which will be used for each column recursively. For
- instance ['green','yellow'] each column's %(kind)s will be filled in
- green or yellow, alternatively. If there is only a single column to
- be plotted, then only the first color from the color list will be
- used.
-
- - A dict of the form {column name : color}, so that each column will be
- colored accordingly. For example, if your columns are called `a` and
- `b`, then passing {'a': 'green', 'b': 'red'} will color %(kind)ss for
- column `a` in green and %(kind)ss for column `b` in red.
- sampling_n: int, default 100:
- Number of random items for plotting.
- sampling_random_state: int, default 0:
- Seed for random number generator.
-
- **kwargs
- Additional keyword arguments are documented in
- :meth:`DataFrame.plot`.
-
- Returns
- -------
- matplotlib.axes.Axes or np.ndarray of them
- An ndarray is returned with one :class:`matplotlib.axes.Axes`
- per column when ``subplots=True``.
-
- Examples
- --------
+ **Examples:**
 
  .. plot::
  :context: close-figs
@@ -118,6 +73,44 @@ def line(
  ... }
  ... )
  >>> ax = df.plot.line(x='one')
+
+ Args:
+ x (label or position, optional):
+ Allows plotting of one column versus another. If not specified,
+ the index of the DataFrame is used.
+ y (label or position, optional):
+ Allows plotting of one column versus another. If not specified,
+ all numerical columns are used.
+ color (str, array-like, or dict, optional):
+ The color for each of the DataFrame's columns. Possible values are:
+
+ - A single color string referred to by name, RGB or RGBA code,
+ for instance 'red' or '#a98d19'.
+
+ - A sequence of color strings referred to by name, RGB or RGBA
+ code, which will be used for each column recursively. For
+ instance ['green','yellow'] each column's %(kind)s will be filled in
+ green or yellow, alternatively. If there is only a single column to
+ be plotted, then only the first color from the color list will be
+ used.
+
+ - A dict of the form {column name : color}, so that each column will be
+ colored accordingly. For example, if your columns are called `a` and
+ `b`, then passing {'a': 'green', 'b': 'red'} will color %(kind)ss for
+ column `a` in green and %(kind)ss for column `b` in red.
+ sampling_n (int, default 100):
+ Number of random items for plotting.
+ sampling_random_state (int, default 0):
+ Seed for random number generator.
+
+ **kwargs:
+ Additional keyword arguments are documented in
+ :meth:`DataFrame.plot`.
+
+ Returns:
+ matplotlib.axes.Axes or np.ndarray of them:
+ An ndarray is returned with one :class:`matplotlib.axes.Axes`
+ per column when ``subplots=True``.
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
@@ -135,30 +128,8 @@ def area(
  of items. For consistent results, the random sampling is reproducible.
  Use the `sampling_random_state` parameter to modify the sampling seed.
 
- Parameters
- ----------
- x : label or position, optional
- Coordinates for the X axis. By default uses the index.
- y : label or position, optional
- Column to plot. By default uses all columns.
- stacked : bool, default True
- Area plots are stacked by default. Set to False to create a
- unstacked plot.
- sampling_n: int, default 100:
- Number of random items for plotting.
- sampling_random_state: int, default 0:
- Seed for random number generator.
- **kwargs
- Additional keyword arguments are documented in
- :meth:`DataFrame.plot`.
-
- Returns
- -------
- matplotlib.axes.Axes or numpy.ndarray
- Area plot, or array of area plots if subplots is True.
-
- Examples
- --------
+ **Examples:**
+
  Draw an area plot based on basic business metrics:
 
  .. plot::
@@ -201,6 +172,26 @@ def area(
  ... 'day': [1, 2, 3],
  ... })
  >>> ax = df.plot.area(x='day')
+
+ Args:
+ x (label or position, optional):
+ Coordinates for the X axis. By default uses the index.
+ y (label or position, optional):
+ Column to plot. By default uses all columns.
+ stacked (bool, default True):
+ Area plots are stacked by default. Set to False to create a
+ unstacked plot.
+ sampling_n (int, default 100):
+ Number of random items for plotting.
+ sampling_random_state (int, default 0):
+ Seed for random number generator.
+ **kwargs:
+ Additional keyword arguments are documented in
+ :meth:`DataFrame.plot`.
+
+ Returns:
+ matplotlib.axes.Axes or numpy.ndarray:
+ Area plot, or array of area plots if subplots is True.
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
@@ -219,55 +210,8 @@ def scatter(
  of items. For consistent results, the random sampling is reproducible.
  Use the `sampling_random_state` parameter to modify the sampling seed.
 
- Parameters
-
- ----------
- x : int or str
- The column name or column position to be used as horizontal
- coordinates for each point.
- y : int or str
- The column name or column position to be used as vertical
- coordinates for each point.
- s : str, scalar or array-like, optional
- The size of each point. Possible values are:
-
- - A string with the name of the column to be used for marker's size.
-
- - A single scalar so all points have the same size.
-
- - A sequence of scalars, which will be used for each point's size
- recursively. For instance, when passing [2,14] all points size
- will be either 2 or 14, alternatively.
- c : str, int or array-like, optional
- The color of each point. Possible values are:
-
- - A single color string referred to by name, RGB or RGBA code,
- for instance 'red' or '#a98d19'.
-
- - A sequence of color strings referred to by name, RGB or RGBA
- code, which will be used for each point's color recursively. For
- instance ['green','yellow'] all points will be filled in green or
- yellow, alternatively.
-
- - A column name or position whose values will be used to color the
- marker points according to a colormap.
- sampling_n: int, default 100:
- Number of random items for plotting.
- sampling_random_state: int, default 0:
- Seed for random number generator.
-
- **kwargs
- Additional keyword arguments are documented in
- :meth:`DataFrame.plot`.
-
- Returns
- -------
- matplotlib.axes.Axes or np.ndarray of them
- An ndarray is returned with one :class:`matplotlib.axes.Axes`
- per column when ``subplots=True``.
-
- Examples
- --------
+ **Examples:**
+
  Let's see how to draw a scatter plot using coordinates from the values
  in a DataFrame's columns.
 
@@ -291,5 +235,50 @@ def scatter(
  ... y='width',
  ... c='species',
  ... colormap='viridis')
+
+
+ Args:
+ x (int or str):
+ The column name or column position to be used as horizontal
+ coordinates for each point.
+ y (int or str):
+ The column name or column position to be used as vertical
+ coordinates for each point.
+ s (str, scalar or array-like, optional):
+ The size of each point. Possible values are:
+
+ - A string with the name of the column to be used for marker's size.
+
+ - A single scalar so all points have the same size.
+
+ - A sequence of scalars, which will be used for each point's size
+ recursively. For instance, when passing [2,14] all points size
+ will be either 2 or 14, alternatively.
+ c (str, int or array-like, optional):
+ The color of each point. Possible values are:
+
+ - A single color string referred to by name, RGB or RGBA code,
+ for instance 'red' or '#a98d19'.
+
+ - A sequence of color strings referred to by name, RGB or RGBA
+ code, which will be used for each point's color recursively. For
+ instance ['green','yellow'] all points will be filled in green or
+ yellow, alternatively.
+
+ - A column name or position whose values will be used to color the
+ marker points according to a colormap.
+ sampling_n (int, default 100):
+ Number of random items for plotting.
+ sampling_random_state (int, default 0):
+ Seed for random number generator.
+
+ **kwargs:
+ Additional keyword arguments are documented in
+ :meth:`DataFrame.plot`.
+
+ Returns:
+ matplotlib.axes.Axes or np.ndarray of them:
+ An ndarray is returned with one :class:`matplotlib.axes.Axes`
+ per column when ``subplots=True``.
  """
  raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)