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Showing posts from May, 2014

First post using stackedit

Welcome to StackEdit! Hey! I’m your first Markdown document in StackEdit 1 . Don’t delete me, I’m very helpful! I can be recovered anyway in the Utils tab of the Settings dialog. Documents StackEdit stores your documents in your browser, which means all your documents are automatically saved locally and are accessible offline! Note: StackEdit is accessible offline after the application has been loaded for the first time. Your local documents are not shared between different browsers or computers. Clearing your browser’s data may delete all your local documents! Make sure your documents are synchronized with Google Drive or Dropbox (check out the Synchronization section). Create a document The document panel is accessible using the button in the navigation bar. You can create a new document by clicking New document in the document panel. Switch to another document All your local documents are listed in the document panel. You can switch from one to anoth

Python for Data Analysis

Publisher: O'Reilly Media Released: October 2012 Pages: 470 Python for Data Analysis  is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language. Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing. Use the IPython interactive shell as your primary development environment Learn basic and advanced NumPy (Numerical Python) features Get started with data analysis tools in the pandas library Use high-