Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills Key FeaturesSpeed up your data analysis projects using powerful R packages and techniquesCreate multiple hands-on data analysis projects using real-world dataDiscover and practice graphical exploratory analysis techniques across domainsBook Description Hands-On Exploratory Data Analysis with R will help you build not just a foundation but also expertise in the elementary ways to analyze data. You will learn how to understand your data and summarize its main characteristics. You'll also uncover the structure of your data, and you'll learn graphical and numerical techniques using the R language. This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will learn how to set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using tools such as DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems. By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, identify hidden insights, and present your results in a business context. What you will learnLearn powerful R techniques to speed up your data analysis projectsImport, clean, and explore data using powerful R packagesPractice graphical exploratory analysis techniquesCreate informative data analysis reports using ggplot2Identify and clean missing and erroneous dataExplore data analysis techniques to analyze multi-factor datasetsWho this book is for Hands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data engineer, software engineer, or product manager, this book will sharpen your skills in the complete workflow of exploratory data analysis.
Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualization Key Features Learn to set up data analysis pipelines with pandas and Jupyter notebooks Effective techniques for data selection, manipulation, and visualization Introduction to Matplotlib for interactive data visualization using charts and plots Book Description The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties. This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats. By the end of this book, you will have a better understanding of exploratory analysis and how to build exploratory data pipelines with Python. What you will learn Learn how to read different kinds of data into pandas DataFrames for data analysis Manipulate, transform, and apply formulas to data imported into pandas DataFrames Use pandas to analyze and visualize different kinds of data to gain real-world insights Extract transformed data form pandas DataFrames and convert it into the formats your application expects Manipulate model time-series data, perform algorithmic trading, derive results on fixed and moving windows, and more Effective data visualization using Matplotlib Who this book is for If you are a budding data scientist looking to learn the popular pandas library, or a Python developer looking to step into the world of data analysis, this book is the ideal resource you need to get started. Some programming experience in Python will be helpful to get the most out of this course
Simplified Python programming for Bitcoin and blockchain Key Features Build Bitcoin applications in Python with the help of simple examples Mine Bitcoins, program Bitcoin-enabled APIs and transaction graphs, and build trading bots Analyze Bitcoin transactions and produce visualizations using Python data analysis tools Book Description Bitcoin is a cryptocurrency that’s changing the face of online payments. Hands-On Bitcoin Programming with Python teaches you to build software applications for mining and creating Bitcoins using Python. This book starts with the basics of both Bitcoin and blockchain and gives you an overview of these inherent concepts by showing you how to build Bitcoin-driven applications with Python. Packed with clear instructions and practical examples, you will learn to understand simple Python coding examples that work with this cryptocurrency. By the end of the book, you’ll be able to mine Bitcoins, accept Bitcoin payments on the app, and work with the basics of blockchain technology to create simply distributed ledgers. What you will learn Master the Bitcoin APIs in Python to manipulate Bitcoin from your Python apps Build your own Bitcoin trading bots to buy Bitcoins at a lower price and sell them at a higher price Write scripts to process Bitcoin payments through a website or app Develop software for Bitcoin mining to create Bitcoin currency on your own computer hardware Create your own keys, addresses, and wallets in Python code Write software to analyze Bitcoin transactions and produce reports, graphs, and other visualizations Who this book is for Hands-On Bitcoin Programming with Python consists of examples that will teach you to build your own Bitcoin application. You will learn to write scripts, build software for mining, and create Bitcoins using Python. Anyone with prior Python experience, who wants to explore Python Bitcoin programming and start building Bitcoin-driven Python apps, will find this book useful.
Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills Key FeaturesSpeed up your data analysis projects using powerful R packages and techniquesCreate multiple hands-on data analysis projects using real-world dataDiscover and practice graphical exploratory analysis techniques across domainsBook Description Hands-On Exploratory Data Analysis with R will help you build not just a foundation but also expertise in the elementary ways to analyze data. You will learn how to understand your data and summarize its main characteristics. You'll also uncover the structure of your data, and you'll learn graphical and numerical techniques using the R language. This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will learn how to set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using tools such as DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems. By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, identify hidden insights, and present your results in a business context. What you will learnLearn powerful R techniques to speed up your data analysis projectsImport, clean, and explore data using powerful R packagesPractice graphical exploratory analysis techniquesCreate informative data analysis reports using ggplot2Identify and clean missing and erroneous dataExplore data analysis techniques to analyze multi-factor datasetsWho this book is for Hands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data engineer, software engineer, or product manager, this book will sharpen your skills in the complete workflow of exploratory data analysis.
This book covers a variety of problems, and offers solutions to some, in: • Statistical state and parameter estimation in nonlinear stochastic dynamical system in both the classical and quantum scenarios. • Propagation of electromagnetic waves in a plasma as described by the Boltzmann Kinetic Transport Equation. • Classical and Quantum General Relativity. It will be of use to Engineering undergraduate students interested in analysing the motion of robots subject to random perturbation, and also to research scientists working in Quantum Filtering.
This book is about several questions regarding how to describe the quantization of the current density in an antenna and about the nature of the quantum electromagnetic field produced by such a quantum current density. The second quantized current density can be built out of the Dirac field of electrons and positrons while the free electromagnetic or photon field is built out of solutions to the wave equation with coefficients being operators, namely the creation and annihilation operators of the photons. Note: T&F does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka.
This book covers the entire span of quantum mechanics whose developments have taken place during the early part of the twentieth century up till the present day. We start with the Rutherford-Bohr model of the atom followed by Schrodinger's wave mechanics with its application to the solution of calculating the energy spectrum of a particle in a box, the harmonic oscillator and finally the hydrogen atom. Heisenberg's matrix mechanics and its duality with Schrodinger's wave mechanics, quantum mechanics in the interaction picture. Dirac's relativistic theory of the electron exhibiting the spin of the electron as a relativistic effect when it interacts with an external electromagnetic field. Feynman's path integral approach to non-relativistic quantum mechanics with is a marvellous intuitive interpretation as a sum over paths and how classical mechanics is obtained from its limit as Planck' constant tends to zero, methods for computing the spectra of the Dirac Hamiltonian in a radial potential, quantum field theory as developed by Feynman, Schwinger, Tomonaga and Dyson for describing the interaction between electrons, positrons, and photons via propagators using both the operator theoretic expansions and Feynman's path integral. We also introduce time independent and time dependent perturbation theory in quantum mechanics with applications to quantum gate design for quantum computers forming a major part of the research conducted by the author's research group, Quantum noise introduced into the Schrodinger and Dirac's equation based on the Hudson-Parthasarathy quantum stochastic calculus in Boson Fock space, scattering theory and wave operators with applications to quantum gate design, some aspects of second quantization like the interpretation of Boson Fock space in terms of harmonic oscillator algebras and the BCS theory of superconductivity, Wigner-Mackey-Frobenius theory of induced representations of a group with applications to Wigner's theory of particle classification, Dirac's equation in a gravitational field and Yang-Mills non-Abelian gauge theories with application to the construction of unified quantum field theories and finally, the more recent theory of super-symmetry which is a Boson-Fermion unification theory. We have discussed the statistics of Boson's, Fermions and Maxwell-Boltzmann based on entropy maximization. The book is written in problem-solution format and it would be of use to physicists and engineers interested respectively in developing unified field theories and in the design of quantum gates. Note: T&F does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka.
This is a reference book for researchers working in the field of general relativity, quantum mechanics and quantum gravity. A major part of the book deals with the formulation of special relativistic mechanics, special relativistic fluid dynamics and its generalization to general relativity where the gravitational field is described by a metric tensor. Emphasis is laid on the fact that the general theory of relativity is of tensorial character under all dieomorphisms of space-time and hence its field equations, namely the Einstein field equations for gravitation, the Maxwell equations in a curved space-time geometry and the fluid dynamical equations in curved space time are all valid for all observers in the universe. The emphasis throughout is on the fact that matter generates a gravitational field described by a metric that has a non-vanishing curvature tensor and hence such space-times are inherently curved, ie, cannot be transformed into Minkowsian form. There is a final section on quantum mechanics and quantum field theory which introduces supersymmetry and quantum gravity to the reader. The reader after going through this book will be sufficiently well equipped to start research in quantum gravity, i.e, background independent physics which is as yet an unsolved problem owing to renormalization problems. Note: T& F does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka.
Advanced Techniques of Analytical Chemistry explains analytical chemistry in an accessible manner for students. The book provides basic and practical knowledge that helps the learner to understand the methods used in conducting experiments. Readers will understand the key concepts of qualitative and quantitative analysis through easy-to-read chapters written for chemistry students.Volume 1 covers the topic of volumetric analysis in detail. Topic-wise chapters introduce the reader to volumetric titrations and then explain the range of titration techniques which include aqueous acid-base titration, non-aqueous titration, redox titration, complexometric titration and some miscellaneous methods like diazotisation titration, Kjeldahl’s method and the oxygen flask combustion method.The combination of basic and advanced methods makes this an ideal textbook for chemistry students at graduate and undergraduate levels as well as an ideal handbook for the laboratory instructor.
This book presents concepts of theoretical physics with engineering applications. The topics are of an intense mathematical nature involving tools like probability and random processes, ordinary and partial differential equations, linear algebra and infinite-dimensional operator theory, perturbation theory, stochastic differential equations, and Riemannian geometry. These mathematical tools have been applied to study problems in mechanics, fluid dynamics, quantum mechanics and quantum field theory, nonlinear dynamical systems, general relativity, cosmology, and electrodynamics. A particularly interesting topic of research interest developed in this book is the design of quantum unitary gates of large size using the Feynman diagrammatic approach to quantum field theory. Through this book, the reader will be able to observe how basic physics can revolutionize technology and also how diverse branches of mathematical physics like large deviation theory, quantum field theory, general relativity, and electrodynamics have many common issues that provide the starting point for unifying the whole of physics, namely in the formulation of Grand Unified Theories (GUTS).
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