For many researchers Python is a first-class tool mainly because of its libraries for storing manipulating & gaining insight from data Several resources exist for individual pieces of this data science stack but only with the Python Data Science Handbook do you get them all-IPython Num Py Pandas Matplotlib Scikit-Learn & other related tools Working scientists & data crunchers familiar with reading & writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues manipulating transforming & cleaning data; visualizing different types of data; & 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 to use IPython & Jupyter provide computational environments for data scientists using Python Num Py
Includes:: the ndarray for efficient storage & manipulation of dense data arrays in Python Pandas features the Data Frame for efficient storage & manipulation of labeledcolumnar data in Python Matplotlib
Includes:: capabilities for a flexible range of data visualizations in Python Scikit-Learn for efficient & clean Python implementations of the most important & established machine learning algorithms