Update _scatterplot.py

Author: LiamConnors

packages/python/plotly/plotly/figure_factory/_scatterplot.py

@@ -851,136 +851,121 @@ def create_scatterplotmatrix(
 ):
     """
     Returns data for a scatterplot matrix;
-    **deprecated**,
-    use instead the plotly.graph_objects trace
-    :class:`plotly.graph_objects.Splom`.
-
-    :param (array) df: array of the data with column headers
-    :param (str) index: name of the index column in data array
-    :param (list|tuple) endpts: takes an increasing sequece of numbers
-        that defines intervals on the real line. They are used to group
-        the entries in an index of numbers into their corresponding
-        interval and therefore can be treated as categorical data
-    :param (str) diag: sets the chart type for the main diagonal plots.
-        The options are 'scatter', 'histogram' and 'box'.
-    :param (int|float) height: sets the height of the chart
-    :param (int|float) width: sets the width of the chart
-    :param (float) size: sets the marker size (in px)
-    :param (str) title: the title label of the scatterplot matrix
-    :param (str|tuple|list|dict) colormap: either a plotly scale name,
-        an rgb or hex color, a color tuple, a list of colors or a
-        dictionary. An rgb color is of the form 'rgb(x, y, z)' where
-        x, y and z belong to the interval [0, 255] and a color tuple is a
-        tuple of the form (a, b, c) where a, b and c belong to [0, 1].
-        If colormap is a list, it must contain valid color types as its
-        members.
-        If colormap is a dictionary, all the string entries in
-        the index column must be a key in colormap. In this case, the
-        colormap_type is forced to 'cat' or categorical
-    :param (str) colormap_type: determines how colormap is interpreted.
-        Valid choices are 'seq' (sequential) and 'cat' (categorical). If
-        'seq' is selected, only the first two colors in colormap will be
-        considered (when colormap is a list) and the index values will be
-        linearly interpolated between those two colors. This option is
-        forced if all index values are numeric.
-        If 'cat' is selected, a color from colormap will be assigned to
-        each category from index, including the intervals if endpts is
-        being used
-    :param (dict) **kwargs: a dictionary of scatterplot arguments
-        The only forbidden parameters are 'size', 'color' and
-        'colorscale' in 'marker'
-
+    **deprecated**. Use [`plotly.graph_objects.Splom`][plotly.graph_objects.Splom] instead.
+
+    Parameters
+    ----------
+    df : array-like
+        Array of the data with column headers.
+    index : str
+        Name of the index column in data array.
+    endpts : list or tuple
+        Takes an increasing sequence of numbers that defines intervals on the real line.
+        They are used to group the entries in an index of numbers into their corresponding
+        interval and therefore can be treated as categorical data.
+    diag : str
+        Sets the chart type for the main diagonal plots. The options are 'scatter', 'histogram' and 'box'.
+    height : int or float
+        Sets the height of the chart.
+    width : int or float
+        Sets the width of the chart.
+    size : float
+        Sets the marker size (in px).
+    title : str
+        The title label of the scatterplot matrix.
+    colormap : str, tuple, list, or dict
+        Either a plotly scale name, an rgb or hex color, a color tuple, a list of colors or a dictionary.
+        An rgb color is of the form 'rgb(x, y, z)' where x, y and z belong to the interval [0, 255] and a color tuple is a
+        tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colormap is a list, it must contain valid color types as its
+        members. If colormap is a dictionary, all the string entries in the index column must be a key in colormap. In this case, the
+        colormap_type is forced to 'cat' or categorical.
+    colormap_type : str
+        Determines how colormap is interpreted. Valid choices are 'seq' (sequential) and 'cat' (categorical). If
+        'seq' is selected, only the first two colors in colormap will be considered (when colormap is a list) and the index values will be
+        linearly interpolated between those two colors. This option is forced if all index values are numeric.
+        If 'cat' is selected, a color from colormap will be assigned to each category from index, including the intervals if endpts is
+        being used.
+    **kwargs : dict
+        A dictionary of scatterplot arguments. The only forbidden parameters are 'size', 'color' and
+        'colorscale' in 'marker'.
+
+    Returns
+    -------
+    plotly.graph_objs._figure.Figure
+        A Plotly figure object representing the scatterplot matrix.
+
+    Examples
+    --------
     Example 1: Vanilla Scatterplot Matrix
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
-
     >>> # Create dataframe
     >>> df = pd.DataFrame(np.random.randn(10, 2),
     ...                 columns=['Column 1', 'Column 2'])
-
     >>> # Create scatterplot matrix
     >>> fig = create_scatterplotmatrix(df)
     >>> fig.show()
 
-
     Example 2: Indexing a Column
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
-
     >>> # Create dataframe with index
     >>> df = pd.DataFrame(np.random.randn(10, 2),
     ...                    columns=['A', 'B'])
-
     >>> # Add another column of strings to the dataframe
     >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple',
     ...                          'grape', 'pear', 'pear', 'apple', 'pear'])
-
     >>> # Create scatterplot matrix
     >>> fig = create_scatterplotmatrix(df, index='Fruit', size=10)
     >>> fig.show()
 
-
     Example 3: Styling the Diagonal Subplots
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
-
     >>> # Create dataframe with index
     >>> df = pd.DataFrame(np.random.randn(10, 4),
     ...                    columns=['A', 'B', 'C', 'D'])
-
     >>> # Add another column of strings to the dataframe
     >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple',
     ...                          'grape', 'pear', 'pear', 'apple', 'pear'])
-
     >>> # Create scatterplot matrix
     >>> fig = create_scatterplotmatrix(df, diag='box', index='Fruit', height=1000,
     ...                                width=1000)
     >>> fig.show()
 
-
     Example 4: Use a Theme to Style the Subplots
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
-
     >>> # Create dataframe with random data
     >>> df = pd.DataFrame(np.random.randn(100, 3),
     ...                    columns=['A', 'B', 'C'])
-
     >>> # Create scatterplot matrix using a built-in
     >>> # Plotly palette scale and indexing column 'A'
     >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A',
     ...                                colormap='Blues', height=800, width=800)
     >>> fig.show()
 
-
     Example 5: Example 4 with Interval Factoring
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
-
     >>> # Create dataframe with random data
     >>> df = pd.DataFrame(np.random.randn(100, 3),
     ...                    columns=['A', 'B', 'C'])
-
     >>> # Create scatterplot matrix using a list of 2 rgb tuples
     >>> # and endpoints at -1, 0 and 1
     >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A',
@@ -990,30 +975,24 @@ def create_scatterplotmatrix(
     ...                                endpts=[-1, 0, 1], height=800, width=800)
     >>> fig.show()
 
-
     Example 6: Using the colormap as a Dictionary
 
     >>> from plotly.graph_objs import graph_objs
     >>> from plotly.figure_factory import create_scatterplotmatrix
-
     >>> import numpy as np
     >>> import pandas as pd
     >>> import random
-
     >>> # Create dataframe with random data
     >>> df = pd.DataFrame(np.random.randn(100, 3),
     ...                    columns=['Column A',
     ...                             'Column B',
     ...                             'Column C'])
-
     >>> # Add new color column to dataframe
     >>> new_column = []
     >>> strange_colors = ['turquoise', 'limegreen', 'goldenrod']
-
     >>> for j in range(100):
     ...     new_column.append(random.choice(strange_colors))
     >>> df['Colors'] = pd.Series(new_column, index=df.index)
-
     >>> # Create scatterplot matrix using a dictionary of hex color values
     >>> # which correspond to actual color names in 'Colors' column
     >>> fig = create_scatterplotmatrix(