Added docstring for radviz

Author: orbitfold

pandas/tools/plotting.py

@@ -147,6 +147,65 @@ def _get_marker_compat(marker):
         return 'o'
     return marker
 
+def radviz(frame, class_column, ax=None, **kwds):
+    """RadViz - a multivariate data visualization algorithm
+
+    Parameters:
+    -----------
+    frame: DataFrame object
+    class_column: Column name that contains information about class membership
+    ax: Matplotlib axis object, optional
+    kwds: Matplotlib scatter method keyword arguments, optional
+
+    Returns:
+    --------
+    ax: Matplotlib axis object
+    """
+    import matplotlib.pyplot as plt
+    import matplotlib.patches as patches
+    import matplotlib.text as text
+    import random
+    def random_color(column):
+        random.seed(column)
+        return [random.random() for _ in range(3)]
+    def normalize(series):
+        a = min(series)
+        b = max(series)
+        return (series - a) / (b - a)
+    column_names = [column_name for column_name in frame.columns if column_name != class_column]
+    columns = [normalize(frame[column_name]) for column_name in column_names]
+    if ax == None:
+        ax = plt.gca(xlim=[-1, 1], ylim=[-1, 1])
+    classes = set(frame[class_column])
+    to_plot = {}
+    for class_ in classes:
+        to_plot[class_] = [[], []]
+    n = len(frame.columns) - 1
+    s = np.array([(np.cos(t), np.sin(t)) for t in [2.0 * np.pi * (i / float(n)) for i in range(n)]])
+    for i in range(len(frame)):
+        row = np.array([column[i] for column in columns])
+        row_ = np.repeat(np.expand_dims(row, axis=1), 2, axis=1)
+        y = (s * row_).sum(axis=0) / row.sum()
+        class_name = frame[class_column][i]
+        to_plot[class_name][0].append(y[0])
+        to_plot[class_name][1].append(y[1])
+    for class_ in classes:
+        ax.scatter(to_plot[class_][0], to_plot[class_][1], color=random_color(class_), label=str(class_), **kwds)
+    ax.add_patch(patches.Circle((0.0, 0.0), radius=1.0, facecolor='none'))
+    for xy, name in zip(s, column_names):
+        ax.add_patch(patches.Circle(xy, radius=0.025, facecolor='gray'))
+        if xy[0] < 0.0 and xy[1] < 0.0:
+            ax.text(xy[0] - 0.025, xy[1] - 0.025, name, ha='right', va='top', size='small')
+        elif xy[0] < 0.0 and xy[1] >= 0.0:
+            ax.text(xy[0] - 0.025, xy[1] + 0.025, name, ha='right', va='bottom', size='small')
+        elif xy[0] >= 0.0 and xy[1] < 0.0:
+            ax.text(xy[0] + 0.025, xy[1] - 0.025, name, ha='left', va='top', size='small')
+        elif xy[0] >= 0.0 and xy[1] >= 0.0:
+            ax.text(xy[0] + 0.025, xy[1] + 0.025, name, ha='left', va='bottom', size='small')
+    ax.legend(loc='upper right')
+    ax.axis('equal')
+    return ax
+
 def andrews_curves(data, class_column, ax=None, samples=200):
     """
     Parameters: