Dmitry Zinoviev's Data Science Essentials in Python: Collect - Organize - PDF

Go from messy, unstructured artifacts kept in SQL and NoSQL databases to a neat, well-organized dataset with this speedy reference for the busy info scientist. comprehend textual content mining, computer studying, and community research; strategy numeric facts with the NumPy and Pandas modules; describe and examine facts utilizing statistical and network-theoretical tools; and spot genuine examples of information research at paintings. This one-stop resolution covers the fundamental facts technological know-how you would like in Python.

Data technology is likely one of the fastest-growing disciplines by way of educational study, scholar enrollment, and employment. Python, with its flexibility and scalability, is instantly overtaking the R language for data-scientific tasks. maintain Python data-science innovations at your fingertips with this modular, speedy connection with the instruments used to obtain, fresh, research, and shop data.

This one-stop answer covers crucial Python, databases, community research, common language processing, parts of desktop studying, and visualization. entry based and unstructured textual content and numeric facts from neighborhood records, databases, and the net. organize, rearrange, and fresh the information. paintings with relational and non-relational databases, information visualization, and easy predictive research (regressions, clustering, and selection trees). See how ordinary information research difficulties are dealt with. and check out your hand at your individual ideas to various medium-scale tasks which are enjoyable to paintings on and glance sturdy in your resume.

Keep this convenient quickly advisor at your part no matter if you are a scholar, an entry-level info technology specialist changing from R to Python, or a pro Python developer who does not are looking to memorize each functionality and option.

What You Need:

You want a first rate distribution of Python 3.3 or above that incorporates no less than NLTK, Pandas, NumPy, Matplotlib, Networkx, SciKit-Learn, and BeautifulSoup. an exceptional distribution that meets the necessities is Anaconda, to be had at no cost from www.continuum.io. for those who plan to establish your personal database servers, you furthermore may desire MySQL (www.mysql.com) and MongoDB (www.mongodb.com). either programs are unfastened and run on home windows, Linux, and Mac OS.