Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for...
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for...
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools.
Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.
With this handbook, you'll learn how:
IPython and Jupyter provide
Chýba alebo je nepravdivý niektorý dôležitý parameter? Uvedené informácie sú len orientačné, pred nákupom vo vybranom obchode odporúčame overiť, že predávaný model má kľúčové vlastnosti podľa vašich požiadaviek. Aj keď sa snažíme o maximálnu presnosť informácií, bohužiaľ nemôžeme zaručiť 100% správnosť. Ceny produktov sú vrátane DPH.
