diff --git a/inaFaceAnalyzer/excel_export.py b/inaFaceAnalyzer/excel_export.py
new file mode 100644
index 0000000..dd460e9
--- /dev/null
+++ b/inaFaceAnalyzer/excel_export.py
@@ -0,0 +1,59 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Jun 26 20:22:00 2023
+
+@author: ddoukhan
+"""
+
+import xlsxwriter
+import cv2
+import os
+from io import BytesIO
+from .opencv_utils import imread_rgb
+from .face_preprocessing import preprocess_face
+
+def excel_export(df, dst, imcol):
+    """
+    df : pandas dataframe corresponding to an analysis
+    dst : output excel filename
+    imcol : name of the column containing the path to the image to display
+    """
+    cols = list(df.columns)
+   
+   
+    # Create an new Excel file and add a worksheet.
+    workbook = xlsxwriter.Workbook(dst)
+    worksheet = workbook.add_worksheet()
+
+    # Widen the first column to make the text clearer.
+    worksheet.set_column('A:A',15)
+    worksheet.set_default_row(80)
+
+   
+    worksheet.write(0, 0, 'face_image')
+    for i, col in enumerate(cols):
+        #print('col', col)
+        worksheet.write(0, i+1, col)
+   
+    for ituple, t in enumerate(df.itertuples(index=False)):
+        #print('line', ituple)
+        for ielt, elt in enumerate(t):
+            #print('ELT', ielt, elt)
+            if isinstance(elt, tuple):
+                elt = str(elt)
+            #print(ielt, elt)
+            worksheet.write(1 + ituple, 1 + ielt, elt)
+       
+        fname = t[cols.index(imcol)]
+        img = imread_rgb(fname)
+        img, _ = preprocess_face(img, None, False, 1, None, (100,100))
+        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+       
+        is_success, buffer = cv2.imencode('.jpg', img)
+        image_data = BytesIO(buffer)
+        worksheet.insert_image(1 + ituple, 0, os.path.basename(fname), {"image_data": image_data})
+
+
+    workbook.close()
+    return None