Big Data phenomenon represents one of the most significant and least visible consequences that rapid expansion of the Internet and technology has brought to us. Data that is generated by the globally connected world is growing at an exponential rate, and embodies a real gold mine for those companies that are capable of successfully implementing big data systems. Companies that most efficiently and effectively employ big data systems will be expected to gain substantial competitive advantage on the market. Data analysis and processing are one of the major components that make big data ecosystem; and in those branches of the data science Python programming language is the most prevalent one because it gives its user-free access to huge amount of constantly updated open source programming libraries and development environments. Namely, in the hands-on section of this thesis we have shown some brief capabilities of the most popular Python programming libraries like Pandas, Scikit-learn, SciPy and Matplotlib which are primarily used for data manipulation, statistics and visualization. Because of all demonstrated in the hands-on section, we hope that we have successfully shown advantages of Python programming language that are primarily reflected in its flexibility and versatility. With few lines of code, the user can transform complex heterogenous and unstructured input information in the logically connected and processable data. Python programming language with its gradual learning curve allows event the most unexperienced users to master its syntax in relatively short period of time; this feature makes Python the most popular programming language for users that are not coming from the IT sector, but want to advance and modernize procedures and tools used in their area of expertise.