ILinePlot: don't call data_frame what's just a python dict

Since the dawn of time we have a "data_frame" variable in ILinePlot that
is actually defined as a pd.Series() but it's acting as a dict.  Rename
it and turn the pd.Series into a dict, as it is simpler and it really is
what this variable moves around.

3 files changed, 20 insertions, 22 deletions

diff --git a/tests/test_plotter.py b/tests/test_plotter.py
index 8a83a09..a2a17f5 100644
--- a/tests/test_plotter.py
+++ b/tests/test_plotter.py
@@ -269,9 +269,7 @@ class TestILinePlotter(unittest.TestCase):
 
         dfr = pd.DataFrame([0, 1, 2, 3], columns=["a"])
         iplot = trappy.ILinePlot(dfr, column=["a"])
-        s = pd.Series()
-        s["s1"] = s1
-        s["s2"] = s2
+        s = {"s1": s1, "s2": s2}
         merged = iplot._fix_indexes(s)
 
         expected_index = index1 + index2
diff --git a/trappy/plotter/ILinePlot.py b/trappy/plotter/ILinePlot.py
index 5449746..84bcb55 100644
--- a/trappy/plotter/ILinePlot.py
+++ b/trappy/plotter/ILinePlot.py
@@ -187,7 +187,7 @@ class ILinePlot(AbstractDataPlotter):
         self._layout = ILinePlotGen(len_pivots, **self._attr)
         plot_index = 0
         for p_val in pivot_vals:
-            data_frame = pd.Series()
+            data_dict = {}
             for constraint in self.c_mgr:
                 if permute:
                     trace_idx, pivot = p_val
@@ -200,7 +200,7 @@ class ILinePlot(AbstractDataPlotter):
 
                 result = constraint.result
                 if pivot in result:
-                    data_frame[legend] = result[pivot]
+                    data_dict[legend] = result[pivot]
 
             if permute:
                 title = self.traces[plot_index].name
@@ -210,8 +210,8 @@ class ILinePlot(AbstractDataPlotter):
                 title = ""
 
             # Fix data frame indexes if necessary
-            data_frame = self._fix_indexes(data_frame)
-            self._layout.add_plot(plot_index, data_frame, title, test=test)
+            data_dict = self._fix_indexes(data_dict)
+            self._layout.add_plot(plot_index, data_dict, title, test=test)
             plot_index += 1
 
         self._layout.finish()
@@ -227,7 +227,7 @@ class ILinePlot(AbstractDataPlotter):
         for constraint in self.c_mgr:
             result = constraint.result
             title = str(constraint)
-            data_frame = pd.Series()
+            data_dict = {}
 
             for pivot in pivot_vals:
                 if pivot in result:
@@ -236,27 +236,27 @@ class ILinePlot(AbstractDataPlotter):
                     else:
                         key = "{0}: {1}".format(self._attr["pivot"], self._attr["map_label"].get(pivot, pivot))
 
-                    data_frame[key] = result[pivot]
+                    data_dict[key] = result[pivot]
 
             # Fix data frame indexes if necessary
-            data_frame = self._fix_indexes(data_frame)
-            self._layout.add_plot(plot_index, data_frame, title)
+            data_dict = self._fix_indexes(data_dict)
+            self._layout.add_plot(plot_index, data_dict, title)
             plot_index += 1
 
         self._layout.finish()
 
-    def _fix_indexes(self, data_frame):
+    def _fix_indexes(self, data_dict):
         """
         In case of multiple traces with different indexes (i.e. x-axis values),
         create new ones with same indexes
         """
         # 1) Check if we are processing multiple traces
-        if len(data_frame) > 1:
+        if len(data_dict) > 1:
             # 2) Merge the data frames to obtain common indexes
-            df_columns = list(data_frame.keys())
-            dedup_data = [handle_duplicate_index(s) for s in data_frame.values]
-            data_frame = pd.Series(dedup_data, index=df_columns)
-            merged_df = pd.concat(data_frame.get_values(), axis=1)
+            df_columns = list(data_dict.keys())
+            dedup_data = [handle_duplicate_index(s) for s in data_dict.values()]
+            ret = pd.Series(dedup_data, index=df_columns)
+            merged_df = pd.concat(ret.get_values(), axis=1)
             merged_df.columns = df_columns
             # 3) Fill NaN values depending on drawstyle
             if self._attr["drawstyle"] == "steps-post":
@@ -271,4 +271,4 @@ class ILinePlot(AbstractDataPlotter):
 
             return merged_df
         else:
-            return data_frame
+            return data_dict
diff --git a/trappy/plotter/ILinePlotGen.py b/trappy/plotter/ILinePlotGen.py
index 13860de..9e3f3f8 100644
--- a/trappy/plotter/ILinePlotGen.py
+++ b/trappy/plotter/ILinePlotGen.py
@@ -182,14 +182,14 @@ class ILinePlotGen(object):
 
         fig_params["pointSize"] = self._attr["point_size"]
 
-    def add_plot(self, plot_num, data_frame, title="", test=False):
+    def add_plot(self, plot_num, data_dict, title="", test=False):
         """Add a plot for the corresponding index
 
         :param plot_num: The linear index of the plot
         :type plot_num: int
 
-        :param data_frame: The data for the plot
-        :type data_frame: :mod:`pandas.DataFrame`
+        :param data_dict: The data for the plot
+        :type data_dict: dict
 
         :param title: The title for the plot
         :type title: str
@@ -197,7 +197,7 @@ class ILinePlotGen(object):
 
         fig_name = self._fig_map[plot_num]
         fig_params = {}
-        fig_params["data"] = json.loads(data_frame.to_json())
+        fig_params["data"] = dict((k, v.T.to_dict()) for k, v in data_dict.iteritems())
         fig_params["name"] = fig_name
         fig_params["rangesel"] = False
         fig_params["logscale"] = False