Re-implementing PR#109 from Marin_Manuel

- Also added Marin Manuel to contributor list

Author: maiyishan

dabest/_classes.py

@@ -175,7 +175,7 @@ def __init__(self, data, idx, x, y, paired, id_col, ci,
 
 
         # Determine the kind of estimation plot we need to produce.
-        if all([isinstance(i, str) for i in idx]):
+        if all([isinstance(i, (str, int, float)) for i in idx]):
             # flatten out idx.
             all_plot_groups = pd.unique([t for t in idx]).tolist()
             if len(idx) > len(all_plot_groups):

dabest/plotter.py

@@ -402,35 +402,24 @@ def EffectSizeDataFramePlotter(EffectSizeDataFrame, **plot_kwargs):
         # Plot the raw data as a slopegraph.
         # Pivot the long (melted) data.
             if color_col is None:
-                pivot_values = yvar
+                pivot_values = [yvar]
             else:
                 pivot_values = [yvar, color_col]
             pivoted_plot_data = pd.pivot(data=plot_data, index=dabest_obj.id_col,
                                          columns=xvar, values=pivot_values)
             x_start = 0
             for ii, current_tuple in enumerate(temp_idx):
-                if len(temp_idx) > 1:
-                    # Select only the data for the current tuple.
-                    if color_col is None:
-                        current_pair = pivoted_plot_data.reindex(columns=current_tuple)
-                    else:
-                        current_pair = pivoted_plot_data[yvar].reindex(columns=current_tuple)
-                else:
-                    if color_col is None:
-                        current_pair = pivoted_plot_data
-                    else:
-                        current_pair = pivoted_plot_data[yvar]
+                current_pair = pivoted_plot_data.loc[:, pd.MultiIndex.from_product([pivot_values, current_tuple])].dropna()
                 grp_count = len(current_tuple)
                 # Iterate through the data for the current tuple.
                 for ID, observation in current_pair.iterrows():
                     x_points = [t for t in range(x_start, x_start + grp_count)]
-                    y_points = observation.tolist()
+                    y_points = observation[yvar].tolist()
 
                     if color_col is None:
                         slopegraph_kwargs['color'] = ytick_color
                     else:
-                        color_key = pivoted_plot_data[color_col,
-                                                      current_tuple[0]].loc[ID]
+                        color_key = observation[color_col][0]
                         if isinstance(color_key, str) == True:
                             slopegraph_kwargs['color'] = plot_palette_raw[color_key]
                             slopegraph_kwargs['label'] = color_key

nbs/02-about.ipynb

@@ -38,6 +38,8 @@
     "\n",
     "- Adam Nekimken ([@anekimken](https://github.com/anekimken)) with [PR #73](https://github.com/ACCLAB/DABEST-python/pull/73): Implement inset axes so estimation plots can be plotted on a pre-determined :py:mod:`matplotlib` :py:class:`Axes` object.\n",
     "\n",
+    "- Marin Manuel ([@MarinManuel](https://github.com/MarinManuel)) with [PR #109](https://github.com/ACCLAB/DABEST-python/pull/109): Fixed bug preventing non-string columns from being used.\n",
+    "\n",
     "\n",
     "\n",
     "## Typography\n",

nbs/API/class.ipynb

@@ -244,7 +244,7 @@
     "\n",
     "\n",
     "        # Determine the kind of estimation plot we need to produce.\n",
-    "        if all([isinstance(i, str) for i in idx]):\n",
+    "        if all([isinstance(i, (str, int, float)) for i in idx]):\n",
     "            # flatten out idx.\n",
     "            all_plot_groups = pd.unique([t for t in idx]).tolist()\n",
     "            if len(idx) > len(all_plot_groups):\n",

nbs/API/plotter.ipynb

@@ -452,35 +452,24 @@
     "        # Plot the raw data as a slopegraph.\n",
     "        # Pivot the long (melted) data.\n",
     "            if color_col is None:\n",
-    "                pivot_values = yvar\n",
+    "                pivot_values = [yvar]\n",
     "            else:\n",
     "                pivot_values = [yvar, color_col]\n",
     "            pivoted_plot_data = pd.pivot(data=plot_data, index=dabest_obj.id_col,\n",
     "                                         columns=xvar, values=pivot_values)\n",
     "            x_start = 0\n",
     "            for ii, current_tuple in enumerate(temp_idx):\n",
-    "                if len(temp_idx) > 1:\n",
-    "                    # Select only the data for the current tuple.\n",
-    "                    if color_col is None:\n",
-    "                        current_pair = pivoted_plot_data.reindex(columns=current_tuple)\n",
-    "                    else:\n",
-    "                        current_pair = pivoted_plot_data[yvar].reindex(columns=current_tuple)\n",
-    "                else:\n",
-    "                    if color_col is None:\n",
-    "                        current_pair = pivoted_plot_data\n",
-    "                    else:\n",
-    "                        current_pair = pivoted_plot_data[yvar]\n",
+    "                current_pair = pivoted_plot_data.loc[:, pd.MultiIndex.from_product([pivot_values, current_tuple])].dropna()\n",
     "                grp_count = len(current_tuple)\n",
     "                # Iterate through the data for the current tuple.\n",
     "                for ID, observation in current_pair.iterrows():\n",
     "                    x_points = [t for t in range(x_start, x_start + grp_count)]\n",
-    "                    y_points = observation.tolist()\n",
+    "                    y_points = observation[yvar].tolist()\n",
     "\n",
     "                    if color_col is None:\n",
     "                        slopegraph_kwargs['color'] = ytick_color\n",
     "                    else:\n",
-    "                        color_key = pivoted_plot_data[color_col,\n",
-    "                                                      current_tuple[0]].loc[ID]\n",
+    "                        color_key = observation[color_col][0]\n",
     "                        if isinstance(color_key, str) == True:\n",
     "                            slopegraph_kwargs['color'] = plot_palette_raw[color_key]\n",
     "                            slopegraph_kwargs['label'] = color_key\n",