Getting Started with Python Data Analysis Phuong Vothihong
Publisher: Packt Publishing
Anaconda is a FREE enterprise-ready Python distribution for data analytics, processing Anaconda comes with Python 2.7 or Python 3.4 GETTING STARTED. This is where the effort you put into getting Python running pays off! Predict survival on the Titanic using Excel, Python, R & Random Forests Submit directly to the competition, no data download or local environment needed! For those who are not The first thing to do is get the data from the Kaggle website. There are many libraries available to perform data analysis in Python. Version Control, Git, and GitHub; Getting Started with Git; Forking; Creating a Branch; Making changes; Pushing your changes. Don't worry This is an amazing book for someone getting started in Matplotlib. Getting started with scikit-learn In this recipe, we introduce the basics of the machine learning scikit-learn package Getting Started with Python Data Analysis. In the previous pandas tutorial you gained the skills to clean and fill in data using the kind of analysis, we now have links to outside tutorials for Getting Started with R. I'm just wondering the pro's and con's of using R compared to python + ML packages. Storing data with PyTables Hierarchical Data Format (HDF) is a specification NumPy: We installed NumPy in Chapter 1, Getting Started with Python Libraries. Getting Started with Excel: Kaggle's Titanic Competition.