  In this article we describe how we successfully incorporated data analysis in
Python in a first-year laboratory course without significantly altering the
course structure and without overburdening students. We show how we created and
used carefully designed Jupyter Notebooks with exercises and physics
application examples that allow students to master data analysis programming in
the laboratory course. We use these Notebooks to guide students through the
fundamentals of data handling and analysis in Python while performing simple
experiments. We present our teaching approach and the developed materials. We
discuss the effectiveness of our intervention based on the results from pre-
and post- course questionnaires and students' group work. The results presented
give insights about advantages and challenges of introducing computation at the
early stage of the curriculum in a laboratory course setting and are
informative for other instructors and the physics education research community.
