Python for Finance

Analyze Big Financial Data

Author: Yves Hilpisch

Publisher: "O'Reilly Media, Inc."

ISBN: 1491945397

Category: Business & Economics

Page: 606

View: 4006

DOWNLOAD NOW »

The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
Release

Comparative Approaches to Using R and Python for Statistical Data Analysis

Author: Sarmento, Rui,Costa, Vera

Publisher: IGI Global

ISBN: 1522519890

Category: Business & Economics

Page: 197

View: 2355

DOWNLOAD NOW »

The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users. Comparative Approaches to using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.
Release

Web Scraping with Python

Collecting Data from the Modern Web

Author: Ryan Mitchell

Publisher: "O'Reilly Media, Inc."

ISBN: 1491910275

Category: Computers

Page: 256

View: 4567

DOWNLOAD NOW »

Learn web scraping and crawling techniques to access unlimited data from any web source in any format. With this practical guide, you’ll learn how to use Python scripts and web APIs to gather and process data from thousands—or even millions—of web pages at once. Ideal for programmers, security professionals, and web administrators familiar with Python, this book not only teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing. Code samples are available to help you understand the concepts in practice. Learn how to parse complicated HTML pages Traverse multiple pages and sites Get a general overview of APIs and how they work Learn several methods for storing the data you scrape Download, read, and extract data from documents Use tools and techniques to clean badly formatted data Read and write natural languages Crawl through forms and logins Understand how to scrape JavaScript Learn image processing and text recognition
Release

Pandas for Everyone

Python Data Analysis

Author: Daniel Y. Chen

Publisher: Addison-Wesley Professional

ISBN: 0134547055

Category: Computers

Page: 416

View: 9779

DOWNLOAD NOW »

The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem. Work with DataFrames and Series, and import or export data Create plots with matplotlib, seaborn, and pandas Combine datasets and handle missing data Reshape, tidy, and clean datasets so they’re easier to work with Convert data types and manipulate text strings Apply functions to scale data manipulations Aggregate, transform, and filter large datasets with groupby Leverage Pandas’ advanced date and time capabilities Fit linear models using statsmodels and scikit-learn libraries Use generalized linear modeling to fit models with different response variables Compare multiple models to select the “best” Regularize to overcome overfitting and improve performance Use clustering in unsupervised machine learning
Release

Mining Social Media

Finding Stories in Internet Data

Author: Lam Thuy Vo

Publisher: No Starch Press

ISBN: 1593279175

Category: Computers

Page: 208

View: 3763

DOWNLOAD NOW »

BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: • Write Python scripts and use APIs to gather data from the social web • Download data archives and dig through them for insights • Inspect HTML downloaded from websites for useful content • Format, aggregate, sort, and filter your collected data using Google Sheets • Create data visualizations to illustrate your discoveries • Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library • Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.
Release

RNA-seq Data Analysis

A Practical Approach

Author: Eija Korpelainen,Jarno Tuimala,Panu Somervuo,Mikael Huss,Garry Wong

Publisher: CRC Press

ISBN: 1466595019

Category: Mathematics

Page: 322

View: 5048

DOWNLOAD NOW »

The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
Release

Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation, Second Edition

Author: Lee Reiber

Publisher: McGraw Hill Professional

ISBN: 1260135101

Category: Computers

Page: N.A

View: 1309

DOWNLOAD NOW »

Master the tools and techniques of mobile forensic investigations Conduct mobile forensic investigations that are legal, ethical, and highly effective using the detailed information contained in this practical guide. Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation, Second Edition fully explains the latest tools and methods along with features, examples, and real-world case studies. Find out how to assemble a mobile forensics lab, collect prosecutable evidence, uncover hidden files, and lock down the chain of custody. This comprehensive resource shows not only how to collect and analyze mobile device data but also how to accurately document your investigations to deliver court-ready documents. •Legally seize mobile devices, USB drives, SD cards, and SIM cards•Uncover sensitive data through both physical and logical techniques•Properly package, document, transport, and store evidence•Work with free, open source, and commercial forensic software•Perform a deep dive analysis of iOS, Android, and Windows Phone file systems•Extract evidence from application, cache, and user storage files•Extract and analyze data from IoT devices, drones, wearables, and infotainment systems•Build SQLite queries and Python scripts for mobile device file interrogation•Prepare reports that will hold up to judicial and defense scrutiny
Release

Animal Genomics

Author: Bhanu P. Chowdhary

Publisher: S Karger Ag

ISBN: N.A

Category: Science

Page: 366

View: 7999

DOWNLOAD NOW »

This publication provides an update on the current status of gene maps in different livestock and pet/companion animal species. The findings summarized in species specific commentaries and original articles testify the rapid advances made in the field of animal genomics. Of significant interest is the fact that current investigations are providing headways for two important and exciting research fronts: targeted high-resolution mapping leading to the application of genomic information in addressing questions of economic and biological significance in animals, and the initiation of whole genome sequencing projects for some of the animal species. Like in humans and mice, this will set the stage for a new level of research and real time complex analysis of the genomes of these species. Animal Genomics signifies the beginning of a new era in this field and celebrates the achievements of the past 20 years of genomics research. It will be of special interest to researchers involved in genome analysis - both gross chromosomal as well as molecular - in various animal species, and to comparative and evolutionary geneticists.
Release