diff --git a/trappy/plotter/AbstractDataPlotter.py b/trappy/plotter/AbstractDataPlotter.py
index e4891d82..0bbc4430 100644
--- a/trappy/plotter/AbstractDataPlotter.py
+++ b/trappy/plotter/AbstractDataPlotter.py
@@ -55,13 +55,13 @@ def _check_data(self):
         data = listify(self.traces)
 
         if len(data):
-            mask = map(lambda x: isinstance(x, DataFrame), data)
-            data_frame = reduce(lambda x, y: x and y, mask)
+            data_frame = all(isinstance(x, DataFrame) for x in data)
             sig_or_template = self.templates or "signals" in self._attr
 
             if not data_frame and not sig_or_template:
                 raise ValueError(
-                    "Cannot understand data. Accepted DataFormats are pandas.DataFrame or trappy.FTrace/BareTrace/SysTrace (with templates)")
+                    "Cannot understand data. Accepted types are pandas.DataFrame"
+                    " or trappy.FTrace/BareTrace/SysTrace (with templates)")
             elif data_frame and "column" not in self._attr:
                 raise ValueError("Column not specified for DataFrame input")
         else:
diff --git a/trappy/plotter/Constraint.py b/trappy/plotter/Constraint.py
index 1a5adc97..9dce3f3b 100644
--- a/trappy/plotter/Constraint.py
+++ b/trappy/plotter/Constraint.py
@@ -212,8 +212,8 @@ class ConstraintManager(object):
 
 
     :param traces: Input Trace data
-    :type traces: :mod:`trappy.trace.BareTrace`, list(:mod:`trappy.trace.BareTrace`)
-        (or a class derived from :mod:`trappy.trace.BareTrace`)
+    :type traces: a list of :mod:`trappy.trace.BareTrace` (or derived class),
+        or :mod:`pandas.DataFrame` or a single instance of them.
     :param columns: The column values from the corresponding
         :mod:`pandas.DataFrame`
     :type columns: str, list(str)
@@ -276,12 +276,17 @@ def _expand(self):
                    Len[columns] != 1
                    Len[templates] != 1
             )
+
+            TODO  is the following correct?
+            Permute(
+                   Len[traces] != 1
+                   Len[columns] = 1
+                   Len[templates] != 1
+            )
         """
         min_len = min(self._lens)
         max_pos_comp = [
-            i for i,
-            j in enumerate(
-                self._lens) if j != self._max_len]
+            i for i, j in enumerate(self._lens) if j != self._max_len]
 
         if self._max_len == 1 and min_len != 1:
             raise RuntimeError("Essential Arg Missing")
diff --git a/trappy/plotter/ILinePlot.py b/trappy/plotter/ILinePlot.py
index 2bcd6aa4..fb26d106 100644
--- a/trappy/plotter/ILinePlot.py
+++ b/trappy/plotter/ILinePlot.py
@@ -36,6 +36,11 @@
 
 class ILinePlot(AbstractDataPlotter):
     """
+    Interactive Line Plotter
+
+    Creates line plots for use in IPython notebooks that can be zoomed and
+    scrolled interactively
+
     This class uses :mod:`trappy.plotter.Constraint.Constraint` to
     represent different permutations of input parameters. These
     constraints are generated by creating an instance of
@@ -46,10 +51,30 @@ class ILinePlot(AbstractDataPlotter):
         :mod:`trappy.trace.SysTrace`, :mod:`trappy.trace.BareTrace`
         or :mod:`pandas.DataFrame` or a single instance of them.
 
-    :param column: specifies the name of the column to
-           be plotted.
+    :param column: When plotting DataFrames, specifies the name of the column to
+           be plotted. If plotting a single DataFrame, may be a list of columns
+           to use. If plotting multiple DataFrames, must be a single column name
+           or a list of respective column names such that ``columns[i]`` is
+           plotted from ``traces[i]`` for each ``i``.
     :type column: (str, list(str))
 
+    :param signals: When plotting traces (i.e. using ``Ftrace``, ``SysTrace`` et
+        al. for ``traces``), a string of the type event_name:column to indicate
+        the value that needs to be plotted.  You can add an additional parameter
+        to specify the color of the line in rgb: "event_name:column:color".  The
+        color is specified as a comma separated list of rgb values, from 0 to
+        255 or from 0x0 to 0xff.  E.g. 0xff,0x0,0x0 is red and 100,40,32 is
+        brown.
+
+        .. note::
+
+            - Only one of `signals` or both `templates` and
+              `columns` should be specified
+            - Signals format won't work for :mod:`pandas.DataFrame`
+              input
+
+    :type signals: str
+
     :param templates: TRAPpy events
 
         .. note::
@@ -113,22 +138,6 @@ class ILinePlot(AbstractDataPlotter):
         you zoom on any plot in a group all plots will zoom at the
         same time.
     :type group: string
-
-    :param signals: A string of the type event_name:column to indicate
-        the value that needs to be plotted.  You can add an additional
-        parameter to specify the color of the lin in rgb:
-        "event_name:column:color".  The color is specified as a comma
-        separated list of rgb values, from 0 to 255 or from 0x0 to
-        0xff.  E.g. 0xff,0x0,0x0 is red and 100,40,32 is brown.
-
-        .. note::
-
-            - Only one of `signals` or both `templates` and
-              `columns` should be specified
-            - Signals format won't work for :mod:`pandas.DataFrame`
-              input
-
-    :type signals: str
     """
 
     def __init__(self, traces, templates=None, **kwargs):
diff --git a/trappy/plotter/Utils.py b/trappy/plotter/Utils.py
index 2a475802..344c981a 100644
--- a/trappy/plotter/Utils.py
+++ b/trappy/plotter/Utils.py
@@ -21,13 +21,17 @@
 from trappy.utils import listify
 
 
-def normalize_list(val, lst):
-    """Normalize a unitary list"""
+def normalize_list(count, lst):
+    """Normalize a unitary list
 
+    :param lst: list with single item
+    :param count: Length of returned list
+    :returns: List containing ``count`` instances of the item in ``list``
+    """
     if len(lst) != 1:
         raise RuntimeError("Cannot Normalize a non-unitary list")
 
-    return lst * val
+    return lst * count
 
 
 def decolonize(val):