diff --git a/examples/dppe/dppe.py b/examples/dppe/dppe.py
index 89fb4f3..5a37c59 100644
--- a/examples/dppe/dppe.py
+++ b/examples/dppe/dppe.py
@@ -7,6 +7,7 @@
 logging.basicConfig(format=FORMAT, level=logging.DEBUG)
 
 import stk
+
 from conformational_sampling.catalytic_reaction_complex import (
     ReductiveEliminationComplex,
 )
@@ -69,6 +70,7 @@
 start_visualization = False
 if start_visualization:
     import panel as pn
+
     from conformational_sampling.visualization import ConformationalSamplingDashboard
 
     pn.serve(
diff --git a/examples/suzuki/suzuki.py b/examples/suzuki/suzuki.py
index c79f550..0f12118 100644
--- a/examples/suzuki/suzuki.py
+++ b/examples/suzuki/suzuki.py
@@ -7,6 +7,7 @@
 logging.basicConfig(format=FORMAT, level=logging.DEBUG)
 
 import stk
+
 from conformational_sampling.catalytic_reaction_complex import (
     ReductiveEliminationComplex,
 )
@@ -63,6 +64,20 @@
     reactive_ligand_2=reactive_ligand_2,
     config=config,
 )
+
+# set to True to start visualization after conformer reaction paths have already
+# been generated
+start_visualization = False
+if start_visualization:
+    import panel as pn
+
+    from conformational_sampling.visualization import ConformationalSamplingDashboard
+
+    pn.serve(
+        ConformationalSamplingDashboard(reactive_complex).app(), show=False, port=5006
+    )
+    raise SystemExit
+
 # generates conformers including multi-phase optimization and uniqueness filtering
 reactive_complex.gen_conformers()
 
diff --git a/src/conformational_sampling/analyze.py b/src/conformational_sampling/analyze.py
index 1e1e830..3e2206a 100644
--- a/src/conformational_sampling/analyze.py
+++ b/src/conformational_sampling/analyze.py
@@ -8,7 +8,7 @@
 import numpy as np
 import stk
 from openbabel import pybel as pb
-from pyGSM.utilities.units import EV_TO_AU, KCAL_MOL_PER_AU
+from pyGSM.utilities.units import EV_TO_AU, KCAL_MOL_PER_AU, KJ_MOL_TO_AU
 from rdkit import Chem
 from rdkit.Chem import rdmolops, rdMolTransforms
 from rdkit.Chem.rdmolfiles import MolFromMolBlock, MolToMolBlock
@@ -114,7 +114,9 @@ def __post_init__(self):
             for node in ob_string_nodes:
                 mol_block = node.write('mol')
                 self.string_nodes.append(MolFromMolBlock(mol_block, removeHs=False))
-                self.string_energies.append(float(mol_block.split()[0]) * EV_TO_AU * KCAL_MOL_PER_AU)
+                # correcting for mismatched units based on the unit conversion in pyGSM
+                # when writing to XYZ files
+                self.string_energies.append(float(mol_block.split()[0]) / KJ_MOL_TO_AU)
         else:
             self.string_nodes = [
                 MolFromMolBlock(node.write("mol"), removeHs=False)
diff --git a/src/conformational_sampling/visualization.py b/src/conformational_sampling/visualization.py
index bfd8b3c..2865cbe 100644
--- a/src/conformational_sampling/visualization.py
+++ b/src/conformational_sampling/visualization.py
@@ -2,37 +2,41 @@
 # %reload_ext autoreload
 # %autoreload 2
 import os
-import re
 import pickle
+import re
+
 # from IPython.display import display
 import numpy as np
 import pandas as pd
 from rdkit import Chem
-from rdkit.Chem.rdchem import Mol
 from rdkit.Chem import rdMolTransforms
-from rdkit.Chem.rdmolfiles import MolToPDBBlock, MolToXYZBlock
+from rdkit.Chem.rdchem import Mol
 from rdkit.Chem.rdMolAlign import AlignMol
+from rdkit.Chem.rdmolfiles import MolToPDBBlock, MolToXYZBlock
 
 print('Made it halfway through imports!')
 
-import param
-import hvplot.pandas # noqa
 import holoviews as hv
-from holoviews import opts, Slope
-from holoviews.streams import Selection1D
+import hvplot.pandas  # noqa
 import panel as pn
-from panel_chemistry.pane import \
-    NGLViewer  # panel_chemistry needs to be imported before you run pn.extension()
+import param
+from holoviews import Slope, opts
+from holoviews.streams import Selection1D
+from panel_chemistry.pane import NGLViewer
+
+# panel_chemistry needs to be imported before you run pn.extension()
 from panel_chemistry.pane.ngl_viewer import EXTENSIONS
+
 pn.extension('bokeh')
 hv.extension('bokeh')
 pn.extension(comms='vscode')
 pn.extension('tabulator')
 pn.extension("ngl_viewer", sizing_mode="stretch_width")
 from pathlib import Path
+
 import openbabel as ob
 
-from conformational_sampling.analyze import Conformer, System, systems, exclude_confs
+from conformational_sampling.analyze import Conformer, System, exclude_confs, systems
 from conformational_sampling.utils import free_energy_diff
 
 print('Finished imports!')
@@ -146,7 +150,7 @@ def dataframe(self):
         )
         
         # self.df.sort_values(axis=0, by='relative_ts_energy (kcal/mol)')['conf_idx'].to_csv(Path.home() / 'confs_df.csv')
-        self.df.to_csv(Path.home() / 'df.csv')
+        self.df.to_csv('conformer_data.csv')
         # return pn.widgets.Tabulator(self.df)
         
         plot = self.df.hvplot(
@@ -172,13 +176,19 @@ def dataframe(self):
         # testing out generating descriptive statistics
         pd.options.display.width = 200
         # self.df.groupby('mol_name').describe().to_csv(Path.home() / 'Lilly' / 'py-conformational-sampling' / 'summary_statistics.csv')
-        sum_stats_file = Path.home() / 'Lilly' / 'py-conformational-sampling' / 'summary_statistics.csv'
+        # sum_stats_file = Path.home() / 'Lilly' / 'py-conformational-sampling' / 'summary_statistics.csv'
         group_by = self.df.groupby(['mol_name', 'Product stereochemistry'])
-        sum_stats = group_by[[
-            'activation energy (kcal/mol)',
-            'relative_ts_energy (kcal/mol)',
-            'forming_bond_torsion (deg)',
-        ]].describe(percentiles=[0.5]).T.to_csv(sum_stats_file, float_format=lambda x: f' {x:.6f}')
+        sum_stats = (
+            group_by[
+                [
+                    'activation energy (kcal/mol)',
+                    'relative_ts_energy (kcal/mol)',
+                    'forming_bond_torsion (deg)',
+                ]
+            ]
+            .describe(percentiles=[0.5])
+            .T.to_csv('summary_statistics.csv', float_format=lambda x: f' {x:.6f}')
+        )
         # sum_stats_file.write_text(sum_stats)
 
         return self.df.hvplot.explorer(