This is a complete tutorial to learn Data Science and Analytics with Python from Scratch. I created this comprehensive guide for beginners who want to learn Data Analysis and Data Science with Python Programming. It is intended for learners who have basic python programming background, and want to apply statistics, machine learning, visualization to gain new insight into data.

Here, you will learn data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. You will also learn basic inferential statistical analysis and Machine learning techniques with scikit-learn ((sklearn).

Too often, we’re not sure how use data to find answers to the questions that will make us more successful. So, this tutorial will help you to discover what data is? And think about what questions you have that can be answered by the data. Based on some open dataset, you will learn to develop a question, describe the variables and their relationships, calculate basic statistics, and present your results clearly.  By the end of this tutorial, you will be able to use python to manage and visualize your data, including how to deal with missing data, variable groups, graphs etc.

Note: I will use Python 3.x, and I will cover only the syntax that is relevant to Python 3.x. for this tutorial. You may use Python 2.7 if you prefer, but you will encounter some differences in the syntax between Python 2.7 and Python 3.x.