Data Analysis. How to Become a Professional

The book covers eight scenarios that any data analyst will inevitably have to deal with. It explains how to work with not only ready-made but also partially processed and fragmented data using the Python language. Tools from popular libraries Pandas and Numpy are reviewed, the issue of bringing unfinished projects to completion is highlighted, and it explains how to build a minimal viable model and test its functionality. Special attention is paid to time series analysis and other data that may change rapidly. For novice data analysts