diff --git a/cellpack/autopack/Analysis.py b/cellpack/autopack/Analysis.py
index d0f09ad6..37b9a6e3 100644
--- a/cellpack/autopack/Analysis.py
+++ b/cellpack/autopack/Analysis.py
@@ -312,9 +312,6 @@ def run_distance_analysis(
                     ]
                 )
 
-            df = pd.DataFrame()
-            df["Ingredient key"] = []
-            df["Pairwise distance distribution"] = []
             img_list = []
             for ingr_key in all_pairwise_distances:
                 ingr_distance_histo_path = figure_path.glob(
@@ -327,11 +324,18 @@ def run_distance_analysis(
                             path=f"{output_image_location}/{img_path.name}",
                         )
                     )
+            text_list = [
+                "Ingredient key",
+                "Pairwise distance distribution",
+                *[
+                    val
+                    for pair in zip(all_pairwise_distances.keys(), img_list)
+                    for val in pair
+                ],
+            ]
+
+            md_object.add_table(header="Pairwise Distance Distributions", table=pd.DataFrame([text_list]))
 
-            df = pd.DataFrame()
-            df["Ingredient key"] = all_pairwise_distances.keys()
-            df["Pairwise distance distribution"] = img_list
-            md_object.add_table(header="", table=df)
 
     def get_ingredient_key_from_object_or_comp_name(
         self, search_name, ingredient_key_dict
@@ -409,6 +413,7 @@ def run_partner_analysis(
         if len(partner_pair_dict):
             md_object.add_header(header="Partner Analysis")
 
+            val_list = []
             paired_keys = []
             touching_radii = []
             binding_probabilities = []
@@ -422,18 +427,38 @@ def run_partner_analysis(
                     numpy.count_nonzero(pairwise_distances < padded_radius)
                     / partner_values["num_packed"]
                 )
-                paired_keys.append(paired_key)
-                touching_radii.append(partner_values["touching_radius"])
-                binding_probabilities.append(partner_values["binding_probability"])
-                close_fractions.append(close_fraction)
+                val_list.extend(
+                    [
+                        paired_key,
+                        partner_values["touching_radius"],
+                        partner_values["binding_probability"],
+                        close_fraction,
+                    ]
+                )
 
-            df = pd.DataFrame()
-            df["Paired keys"] = paired_keys
-            df["Touching radii"] = touching_radii
-            df["Binding probabilities"] = binding_probabilities
-            df["Close packing fractions"] = close_fractions
+            text_list = [
+                "Partner pair",
+                "Touching radius",
+                "Binding probability",
+                "Close packed fraction",
+                *val_list,
+            ]
+            md_object.add_table(
+                header="",
+                text=text_list,
+            )
+                # paired_keys.append(paired_key)
+                # touching_radii.append(partner_values["touching_radius"])
+                # binding_probabilities.append(partner_values["binding_probability"])
+                # close_fractions.append(close_fraction)
 
-            md_object.add_table(header="", table=df)
+            # df = pd.DataFrame()
+            # df["Paired keys"] = paired_keys
+            # df["Touching radii"] = touching_radii
+            # df["Binding probabilities"] = binding_probabilities
+            # df["Close packing fractions"] = close_fractions
+
+            # md_object.add_table(header="", table=df)
 
     def create_report(
         self,
@@ -460,7 +485,23 @@ def create_report(
         run_*_analysis: bool
             whether to run specific analysis
         """
-        self.ingredient_key_dict = self.read_dict_from_glob_file("ingredient_key_*")
+        if report_output_path is None:
+            report_output_path = self.output_path
+        report_output_path = Path(report_output_path)
+
+        # initialize MarkdownWriter object
+        md_object = MarkdownWriter(
+            title="Packing analysis report",
+            output_path=self.output_path,
+            output_image_location=output_image_location,
+            report_name="analysis_report",
+        )
+
+        md_object.add_header(
+            header=f"Analysis for packing results located at {self.packing_results_path}", level=2
+        )
+        if not hasattr(self, "ingredient_key_dict"):
+            self.ingredient_key_dict = self.read_dict_from_glob_file("ingredient_key_*")
 
         if ingredient_keys is None:
             ingredient_keys = list(self.ingredient_key_dict.keys())
@@ -469,38 +510,33 @@ def create_report(
             ingredient_keys=ingredient_keys
         )
         ingredient_radii = self.get_ingredient_radii(recipe_data=recipe_data)
-        pairwise_distance_dict = self.read_dict_from_glob_file(
-            "pairwise_distances_*.json"
-        )
-        combined_pairwise_distance_dict = self.combine_results_from_seeds(
-            pairwise_distance_dict
-        )
+
+
         if not hasattr(self, "pairwise_distance_dict"):
             self.pairwise_distance_dict = self.read_dict_from_glob_file(
                 "pairwise_distances_*.json"
             )
 
-        df = pd.DataFrame()
-        df["Ingredient name"] = list(ingredient_keys)
-        df["Encapsulating radius"] = list(ingredient_radii.values())
-        df["Average number packed"] = list(avg_num_packed.values())
-
-        # path to save report and other outputs
-        if output_image_location is None:
-            output_image_location = self.output_path
-
-        md_object = MarkdownWriter(
-            title="Packing analysis report",
-            output_path=self.output_path,
-            output_image_location=output_image_location,
-            report_name="analysis_report",
+        combined_pairwise_distance_dict = self.combine_results_from_seeds(
+            self.pairwise_distance_dict
         )
 
-        md_object.add_header(
-            header=f"Analysis for packing results located at {self.packing_results_path}"
-        )
+        val_list = []
+        for key, radius, num_packed in zip(ingredient_keys, ingredient_radii.values(), avg_num_packed.values()):
+            val_list.extend([key, radius, num_packed])
+        text_list = [
+            "Ingredient name",
+            "Encapsulating radius",
+            "Average number packed",
+            *val_list,
+        ]
+        # table_data = pd.DataFrame({
+        #     "Ingredient name": list(ingredient_keys),
+        #     "Encapsulating radius": list(ingredient_radii.values()),
+        #     "Average number packed": list(avg_num_packed.values())
+        # })
+        md_object.add_table(header="Ingredient Analysis", table=pd.DataFrame([text_list]))
 
-        # TODO: check if this is needed
         # path to save report and other outputs
         if output_image_location is None:
             output_image_location = self.output_path
@@ -509,6 +545,7 @@ def create_report(
         packing_results_path = self.packing_results_path
         figure_path = packing_results_path / "figures"
 
+        # add packing image to report
         md_object.add_images(
             header="Packing image",
             image_text=["Packing image"],