Data Analysis

Introduction> Introduction # Many data analysis, big data, and machine learning projects require scraping websites to gather the data that you’ll be working with. The Python programming language is widely used in the data science community, and therefore has an ecosystem of modules and tools that you can use in your own projects.

The author selected the Open Internet/Free Speech fund to receive a donation as part of the Write for DOnations program. Introduction> Introduction # A large amount of data that is generated today is unstructured, which requires processing to generate insights.

Introduction> Introduction # Anaconda is an open-source package manager, environment manager, and distribution of the Python and R programming languages. It is commonly used for large-scale data processing, scientific computing, and predictive analytics, serving data scientists, developers, business analysts, and those working in DevOps.

Introduction> Introduction # Machine learning is a research field in computer science, artificial intelligence, and statistics. The focus of machine learning is to train algorithms to learn patterns and make predictions from data.

Introduction> Introduction # Jupyter Notebook is an open-source web application that lets you create and share interactive code, visualizations, and more. This tool can be used with several programming languages, including Python, Julia, R, Haskell, and Ruby.

Introduction> Introduction # Jupyter Notebook offers a command shell for interactive computing as a web application. The tool can be used with several languages, including Python, Julia, R, Haskell, and Ruby.

Introduction> Introduction # The web provides us with more data than any of us can read and understand, so we often want to work with that information programmatically in order to make sense of it.

Introduction> Introduction # Designed for data science and machine learning workflows, Anaconda is an open-source package manager, environment manager, and distribution of the Python and R programming languages. It is commonly used for large-scale data processing, scientific computing, and predictive analytics.

Introduction> Introduction # Python is great for processing data. Often a data set will include multiple variables and many instances, making it hard to get a sense of what is going on.

Introduction> Introduction # The Python pandas package is used for data manipulation and analysis, designed to let you work with labeled or relational data in an intuitive way. The pandas package offers spreadsheet functionality, but because you’re working with Python, it is much faster and more efficient than a traditional graphical spreadsheet program.

Introduction> Introduction # Time series provide the opportunity to forecast future values. Based on previous values, time series can be used to forecast trends in economics, weather, and capacity planning, to name a few.