diff --git a/README.md b/README.md
index d39db5e..b2e5878 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@ Swegram is a tool that offers the ability to annotate and analyse Swedish and En
 
 
 ## Setup ENVIRONMENT VARIABLES
-```console
+```bash
 export SWEGRAM_WORKSPACE=$(pwd)
 ```
 
@@ -14,12 +14,12 @@ export SWEGRAM_WORKSPACE=$(pwd)
 ## Install swegram command line interface
 
 Before installation, it is strongly recommended to use a virtual environment
-```
+```bash
 python3 -m venv venv
 source venv/bin/activate
 ```
 
-```console
+```bash
 # Install swegram package
 pip install swegram --upgrade
 
diff --git a/setup.py b/setup.py
index 1fcf5c2..f9435cc 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 from pathlib import Path
 from setuptools import setup, find_packages
 from typing import List
-
+from swegram_main.version import VERSION
 
 Base = Path(__file__).parent.resolve()
 
@@ -15,7 +15,7 @@ def get_requirements() -> List[str]:
 
 setup(
     name="swegram",
-    version="1.0.2",
+    version=VERSION,
     description="CLI library for Swegram",
     long_description=(Base / "README.md").read_text(encoding="utf-8"),
     packages=find_packages(exclude=["tools*", "test*", "swegram/*", "swegram_django*"]),
diff --git a/setup.sh b/setup.sh
index 295bd71..e279e2a 100644
--- a/setup.sh
+++ b/setup.sh
@@ -1,5 +1,5 @@
+#!/bin/bash
 
 # setup environment variables
-
 export PYTHONPATH="$PYTHONPATH:$(pwd):$(pwd)/tools/efselab"
 export SWEGRAM_WORKSPACE=$(pwd)
diff --git a/swegram_main/handler/visualization.py b/swegram_main/handler/visualization.py
index 981c48d..126d695 100644
--- a/swegram_main/handler/visualization.py
+++ b/swegram_main/handler/visualization.py
@@ -67,7 +67,7 @@ def filter(
         self.outfile_name = self.outdir.joinpath(f"statistic-{self.input_path.with_suffix(f'.{save_as}').name}")
         if save_as == "txt" or pprint:
             self.save(data)
-        elif save_as == "json":
+        if save_as == "json":
             with open(self.outfile_name, code="w", encoding="utf-8") as output_file:
                 data["metadata"] = self.get_json_info()
                 json_object = json.dumps(self.serialize_json_data(data), indent=4)
@@ -152,8 +152,9 @@ def save(self, data: OrderedDict) -> None:
                 print()
 
     def save_instance(self, index: Optional[str], unit: str, aspect_instances: List[OrderedDict]) -> None:
+        self._save_instance_head()
         for aspect_name, instance in zip(self.aspects, aspect_instances):
-            self.save_title(unit, aspect_name, index)
+            self.save_aspect_title(unit, aspect_name, index)
             for fn, f in instance.items():
                 self.save_feature(fn, f)
             if self.pprint:
@@ -163,7 +164,7 @@ def save_instance(self, index: Optional[str], unit: str, aspect_instances: List[
         if self.save_as == "txt":
             self.append_in_text("")
 
-    def save_title(self, unit: str, aspect_name: str, index: Optional[str]) -> None:
+    def save_aspect_title(self, unit: str, aspect_name: str, index: Optional[str]) -> None:
         title = f"{' ':>2}{'-'.join(e for e in (unit.title(), index, aspect_name) if e):>40}" \
                 f"{'|':>4}{'-'*13}|{'-'*13}|{'-'*13}|"
         if self.pprint:
@@ -181,6 +182,18 @@ def c(v: Any) -> Any:
         if self.save_as == "txt":
             self.append_in_text(feature)
 
+    def _save_instance_head(self):
+        af = "UNIT-ASPECT/Features"
+        scalar = "Scalar"
+        mean = "Mean"
+        median = "Median"
+
+        heading = f"{' ':>2}{af:>40}{'|':>4}{scalar:>10}{'|':>4}{mean:>10}{'|':>4}{median:>10}{'|':>4}"
+        if self.pprint:
+            print(heading)
+        if self.save_as == "txt":
+            self.append_in_text(heading)
+
 
 class XlsxStatisticWriter(XlsxClient):
 
@@ -210,7 +223,8 @@ def load_unit(self, unit: str, aspects: Any) -> None:
     def load_aspects(self, sheet: worksheet, row: int, unit: str, aspects: Any) -> int:
         if isinstance(aspects[0], OrderedDict):
             for aspect, features in zip(self.aspects, aspects):
-                self.dump_cell(sheet, row, 1, f"{unit}-{aspect}")
+                for col, content in enumerate([f"{unit}-{aspect}", "Scalar", "Mean", "Median"], 1):
+                    self.dump_cell(sheet, row, col, content)
                 row += 1
                 for feature_name, feature in features.items():
                     self.dump_column_list(sheet, row, 1, [feature_name, feature.scalar, feature.mean, feature.median])
diff --git a/swegram_main/version.py b/swegram_main/version.py
new file mode 100644
index 0000000..18f1193
--- /dev/null
+++ b/swegram_main/version.py
@@ -0,0 +1,3 @@
+"""version module"""
+
+VERSION = "1.0.3"