diff --git a/content/conf.py b/content/conf.py
index 5ef85587..04c8575f 100644
--- a/content/conf.py
+++ b/content/conf.py
@@ -40,9 +40,16 @@
     'sphinx.ext.mathjax',
     'sphinx_aaltoscicomp_branding',
     'sphinxext.opengraph',
+    'sphinx_thebe',
 ]
 myst_enable_extensions = ['colon_fence']
 
+thebe_config = {
+   "selector": "div.highlight"
+}
+
+nb_execution_mode = "off"
+
 ogp_site_name = "Python for Scientific Computing"
 ogp_site_url = 'https://aaltoscicomp.github.io/python-for-scicomp/'
 import datetime
diff --git a/content/pandas.rst b/content/pandas.rst
index 10f97f80..e2b2ec20 100644
--- a/content/pandas.rst
+++ b/content/pandas.rst
@@ -33,6 +33,8 @@ material, including:
 A quick Pandas preview
 ----------------------
 
+.. thebe-button::
+
 Let's get a flavor of what we can do with pandas (you won't be able to follow everything yet). We will be working with an example dataset containing the passenger list from the Titanic, which is often used in Kaggle competitions and data science tutorials. First step is to load pandas::
 
     import pandas as pd
diff --git a/requirements.txt b/requirements.txt
index 0477043c..695dd323 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -6,6 +6,7 @@ sphinx-lesson
 https://github.com/aaltoscicomp/sphinx-aaltoscicomp-branding/archive/master.zip
 sphinx_rtd_theme_ext_color_contrast
 sphinxext-opengraph
+sphinx-thebe
 
 # for web-apis execution
 jsonlines