Nowadays, many software tools for data analysis are available. Many of these are commercial, requiring a paid license or subscription. However, alongside these, there are free alternatives based on open-source software. There is often reluctance toward open-source solutions due to the misconception that freely available code might be lower quality than paid services. This bias is unfounded when considering the scientific communities behind many open-source data analysis frameworks. In this chapter, we will introduce the use of the ROOT data analysis framework, developed at CERN in collaboration with various international institutions, as well as Python and its extensive ecosystem, including Jupyter Notebook. We will also touch on the possibility of combining the capabilities of ROOT with the versatility of the Python programming environment. Open-source code is not entirely free—the true cost is the required knowledge. We encourage the reader to invest in gaining that expertise.