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Python 3 And Data Analytics Pocket Primer
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Book Synopsis Python 3 and Data Analytics Pocket Primer by : Oswald Campesato
Download or read book Python 3 and Data Analytics Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2021-03-19 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at [email protected]. FEATURES: Includes a concise introduction to Python 3 Provides a thorough introduction to data and data cleaning Covers NumPy and Pandas Introduces statistical concepts and data visualization (Matplotlib/Seaborn) Features an appendix on regular expressions Includes companion files with source code and figures
Book Synopsis Data Science Fundamentals Pocket Primer by : Oswald Campesato
Download or read book Data Science Fundamentals Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2021-05-12 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra Provides a thorough introduction to data visualization and regular expressions Covers NumPy, Pandas, R, and SQL Introduces probability and statistical concepts Features numerous code samples throughout Companion files with source code and figures
Book Synopsis Python Tools for Data Scientists Pocket Primer by : Oswald Campesato
Download or read book Python Tools for Data Scientists Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-10-21 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available. FEATURES: Introduces Python, NumPy, Sklearn, SciPy, and awk Covers data cleaning tasks and data visualization Features numerous code samples throughout Includes companion files with source code
Book Synopsis Python 3 and Data Visualization by : Oswald Campesato
Download or read book Python 3 and Data Visualization written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2023-10-03 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python 3 and Data Visualization offers readers a deep dive into the world of Python 3 programming and the art of data visualization. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic data types, loops, and functions to more advanced constructs like dictionaries, sets, and matrices. In Chapter 2, the focus shifts to NumPy and its powerful array operations, seamlessly leading into the world of data visualization using prominent libraries such as Matplotlib. Chapter 6 immerses the reader in Seaborn's rich visualization tools, offering insights into datasets like Iris and Titanic. The appendix covers other visualization tools and techniques, including SVG graphics, D3 for dynamic visualizations, and more. The book also includes companion files with numerous Python code samples and figures. From foundational Python concepts to the intricacies of data visualization, this book serves as a comprehensive resource for both beginners and seasoned professionals. FEATURES: Covers numerous tools for mastering visualization including NumPy, Pandas, SQL, Matplotlib, and Seaborn Includes an introductory chapter on Python 3 basics Features companion files with numerous Python code samples and figures
Book Synopsis Dealing With Data Pocket Primer by : Oswald Campesato
Download or read book Dealing With Data Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-05-04 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of managing data using a variety of computer languages and applications. It is intended to be a fast-paced introduction to some basic features of data management and covers statistical concepts, data-related techniques, features of Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. Companion files with source code and color figures are available. FEATURES: Covers Pandas, RDBMS, NLP, data cleaning, SQL, and data visualization Introduces probability and statistical concepts Features numerous code samples throughout Includes companion files with source code and figures
Download or read book Pandas Basics written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-12-07 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks using Pandas and NumPy. It contains a variety of code samples and features of NumPy and Pandas, and how to write regular expressions. Chapter 3 includes fundamental statistical concepts and Chapter 7 covers data visualization with Matplotlib and Seaborn. Companion files with code are available for downloading from the publisher. FEATURES: Provides the reader with numerous code samples for Pandas and NumPy programming concepts, and an introduction to statistical concepts and data visualization Includes an introductory chapter on Python Companion files with code
Book Synopsis Python for TensorFlow Pocket Primer by : Oswald Campesato
Download or read book Python for TensorFlow Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2019-05-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Dataset refers to the classes in the tf.data.Dataset namespace that enables programmers to construct a pipeline of data by means of method chaining so-called lazy operators, e.g., map(), filter(), batch(), and so forth, based on data from one or more data sources. Companion files with source code are available for downloading from the publisher by writing [email protected]. Features: A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.x Contains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topics Includes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operators Assumes the reader has very limited experience Companion files with all of the source code examples (download from the publisher)
Book Synopsis Python Data Analytics by : Ethan Williams
Download or read book Python Data Analytics written by Ethan Williams and published by . This book was released on 2020-05-27 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction 1PYTHON DATA ANALYTICS - The Ultimate Guide to Learn Python Data AnalyticsHave you ever thought about data analytics? Are you looking for an excellent tool to use in your data analysis? Well, you have come to the right place. Python is one of the best tools that you can use for your data analysis for several reasons;Flexibility & Ease of learning If you are trying something creative that no one has ever done before, then Python is the best way to go. It also ideal for any developer that is looking for a program that will allow them to script websites and applications. The best thing that I love about Python is its readability and simplicity, which goes a long way in boosting a gradual and relatively low learning curve. It is open source This means that Python is an open-source program that also has built a valuable community-based model. It is designed to run on different OS ranging from Windows to Linux environments. The good thing with this language is that you can easily port it to a wide range of platforms. It is well-supported Did you know that anything that could go wrong goes wrong? Think about it, if you are using something that you did not have to pay for, will you get the help that you need quickly? Well, the truth is a definite-NO!Introduction 2PYTHON DATA ANALYTICS - Comprehensive Guide of Tips and Tricks using Python Data Analytics TheoriesHave you always wondered what it is that you can do with the vast volumes of data that you have collected? Is there some way to make it easier to visualize the data to understand it better? If you answered yes to these questions, you have come to the right place. Data can be collected from different sources and devices, and it is important to understand and analyze that data. The data collected has a lot of information that will need to be uncovered to make better decisions in the future. Before you look at the different types of data analytics, it is important that you understand what big data isThis book will help you learn more about how you can do this.Throughout the book, you will gather information about: -What is data, and the different forms of data-An introduction to big data, big data analytics and data science -An in-depth analysis and understanding of big data analytics-The differences between big data, data science and data analytics-An introduction to Python-How to work with functions, strings and data structures-Understanding data mining-What data integration is-How to work on predictive analytics-Developing a simple linear regression, multiple regression, and classification algorithm in PythonThis book will help you learn more about data analytics and what you can use it for. So, what are you waiting for? Grab a copy of this book to get started today.Introduction 3PYTHON DATA ANALYTICS - Advanced and Effective Strategies of Using Python Data AnalyticsDoes your business have large volumes of data that nobody knows how to use? Do you collect data from various sources to perform the analysis? Have you always wondered what you should do with incorrect data sets? If you answered yes, then you have come to the right place. You will learn the different processes and steps you must take to analyze different types of data. In this book, you will learn more about: -What is data analytics, and why is it important?-The different types of data analytics-The process -Different algorithms used to perform data analytics-Identifying different sources of data and mining the required information -Preparing the data-Visualizing the data-An introduction to Python -Using Python to clean and manipulate data-Developing a simple predictive model in PythonYou will learn all this and more in the book. So, what are you waiting for? Grab a copy of this book now.
Download or read book Python Programming written by Jason Test and published by . This book was released on 2020-08-03 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your business thanks to the web applications? If so, keep reading: this bundle book is for you! Finally on launch the most complete Python guide with 3 Manuscripts in 1 book: 1-Python for beginners 2-Python for Data Science 4-Python Crash Course Python will introduce you many selected practices for coding . You will discover as a beginner the world of data science, machine learning and artificial intelligence. The following list is just a tiny fraction of what you will learn in this collection bundle. 1) Python for beginners ✓ The basics of Python programming ✓ Differences among programming languages ✓ Vba, SQL, R, Python ✓ Game creation with Pyhton ✓ Easy-to-follow steps for reading and writing codes. ✓ Control flow statements and Error handling ✓ 4 best strategies with NumPy, Pandas, Matplotlib 2) Python for Data science ◆ 4 reason why Python is fundamental for Data Science ◆ Python design patterns ◆ How to use Python Data Analysis in your business ◆ Data visualization optimal tools and techniques ◆ Analysis of popular Python projects templates ◆ How to set up the Python environment for Data Science ◆ Most important Machine Learning Algorithms ◆ How to leverage Data Science in the Cloud 3) Python Crash Course * A Proven Method to Write your First Program in 7 Days * 5 Common Mistakes to Avoid when You Start Coding * A Simple Strategy to Write Clean, Understandable and Flexible Codes * The One Thing You Need to Debug your Codes in Python * 5 Practical exercises to start programming Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Examples and step-by-step guides will guide you during the code-writing learning process. The description of each topic is crystal-clear and you can easily practice with related exercises. You will also learn all the best tricks of writing codes with point by point descriptions of the code elements. If you really wish to to learn Python and master its language, please click the BUY NOW button.
Download or read book Python written by TechExp Academy and published by . This book was released on 2021-01-20 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to learn Python Programming well and fast? Are you looking for the best Python for Data Analysis and Analytics course? Do you want to learn Data Science and how to leverage Python for it? Do want to learn Python Machine Learning and start implementing models? If yes, then this Python for Beginners Crash Course is for you. This is the most complete Python guide with 5 Manuscripts in 1 book: 1-Python For Beginners 2-Python Advanced Programming 3-Python for Data Analysis & Analytics 4-Python for Data Science 5-Python Machine Learning 450+ Pages of Pure Learning! A great opportunity: Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples. In Manuscripts 1 and 2 "Python For Beginners" and "Python Advanced Programming" you'll learn: - What is Python - How to install Python and what is the best distribution - What are data types and variables - How to work with numbers in Python - What operators there are in Python and when to use them - How to manipulate Strings - How to implement Program Flow Controls - How to implement loops in Python - What are Python lists, Tuples, Sets, Dictionaries, and how to use them - How to create modules and functions - How to program according to the Object-Oriented paradigm - How to create classes - What are and how to use Inheritance, Polymorphism, Abstraction, and Encapsulation And much more... In Manuscript 3 "Python for Data Analysis & Analytics" you'll learn: - What Data Analysis is and why it is important - What are the different types of Data Analysis - What are the 6 key steps of the Data Analysis process that you should follow - What are the applications of Data Analysis and Analytics - How to set up the Python environment for Data Analysis - What are and how to use Python Data Structures - How to work with IPython/Jupyter Notebook - How to work with NumPy - How to visualize data with Matplotlib - What other visualization libraries are out there - Why is Big Data important and how to get the best out of it - How to leverage Neural Networks for Data Analysis And much more... In Manuscript 4 "Python for Data Science" you'll learn: - What is Data Science and what does it encompass - What are the 5 key steps of the Data Science process that you should follow - How to set up the Python environment for Data Science - How to work with Seaborn data visualization module - What are the most important Machine Learning Algorithms - How to leverage the Scikit-Learn module for Machine Learning - How to leverage Data Science in the Cloud - What are the most important applications of Data Science And much more... In Manuscript 5 "Python Machine Learning" you'll learn - What is Machine Learning and what does it encompass - What are the 7 Steps of the Machine Learning Process - What are the different Machine Learning types - How is Machine Learning applied to the real world - What are the main Data Mining techniques - How to best set up the Python environment for Machine Learning - What are the most important Python libraries for Machine Learning And much more... Click the BUY button and download the book now to start learning well and fast!
Book Synopsis Python Data Analytics by : Fabio Nelli
Download or read book Python Data Analytics written by Fabio Nelli and published by Apress. This book was released on 2015-08-25 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language. You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allow you to predict future patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serves as an introduction to Python for data-intensive applications.
Book Synopsis Hands-On Data Preprocessing in Python by : Roy Jafari
Download or read book Hands-On Data Preprocessing in Python written by Roy Jafari and published by Packt Publishing Ltd. This book was released on 2022-01-21 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get your raw data cleaned up and ready for processing to design better data analytic solutions Key FeaturesDevelop the skills to perform data cleaning, data integration, data reduction, and data transformationMake the most of your raw data with powerful data transformation and massaging techniquesPerform thorough data cleaning, including dealing with missing values and outliersBook Description Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who's developed college-level courses on data preprocessing and related subjects. With this book, you'll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you'll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools. What you will learnUse Python to perform analytics functions on your dataUnderstand the role of databases and how to effectively pull data from databasesPerform data preprocessing steps defined by your analytics goalsRecognize and resolve data integration challengesIdentify the need for data reduction and execute itDetect opportunities to improve analytics with data transformationWho this book is for This book is for junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data. You don't need any prior experience with data preprocessing to get started with this book. However, basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are a prerequisite.
Book Synopsis Python Data Analysis by : Avinash Navlani
Download or read book Python Data Analysis written by Avinash Navlani and published by Packt Publishing Ltd. This book was released on 2021-02-05 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand data analysis pipelines using machine learning algorithms and techniques with this practical guide Key FeaturesPrepare and clean your data to use it for exploratory analysis, data manipulation, and data wranglingDiscover supervised, unsupervised, probabilistic, and Bayesian machine learning methodsGet to grips with graph processing and sentiment analysisBook Description Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you'll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you'll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You'll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you'll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you'll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you'll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data. What you will learnExplore data science and its various process modelsPerform data manipulation using NumPy and pandas for aggregating, cleaning, and handling missing valuesCreate interactive visualizations using Matplotlib, Seaborn, and BokehRetrieve, process, and store data in a wide range of formatsUnderstand data preprocessing and feature engineering using pandas and scikit-learnPerform time series analysis and signal processing using sunspot cycle dataAnalyze textual data and image data to perform advanced analysisGet up to speed with parallel computing using DaskWho this book is for This book is for data analysts, business analysts, statisticians, and data scientists looking to learn how to use Python for data analysis. Students and academic faculties will also find this book useful for learning and teaching Python data analysis using a hands-on approach. A basic understanding of math and working knowledge of the Python programming language will help you get started with this book.
Book Synopsis Python for Data Analysis by : Andrew Park
Download or read book Python for Data Analysis written by Andrew Park and published by Andrew Park. This book was released on 2021-04-22 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! NOW at $41,97 instead of $51,97!Do you want to learn more about Data Analysis and how to master it with Python?Your Customers Will Love This Amazing Guide! Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future. Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Pandas, Jupyter and PyTorch The 7 Python libraries that make Python one of the best choices for Data Analysis Neural Network How Data Visualization and Matplotlib can help you to understand the data you are working with. Some of the main industries that are using data to improve their business with 14 real-world applications And Much More! While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics. Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications. Would You Like To Know More? Buy it NOW and Let Your Customers Get Addicted to This Amazing Book!
Book Synopsis Python Data Analysis by : Ivan Idris
Download or read book Python Data Analysis written by Ivan Idris and published by Packt Publishing Ltd. This book was released on 2014-10-28 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Book Synopsis Python Data Analytics by : Fabio Nelli
Download or read book Python Data Analytics written by Fabio Nelli and published by Apress. This book was released on 2018-09-27 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. What You'll LearnUnderstand the core concepts of data analysis and the Python ecosystem Go in depth with pandas for reading, writing, and processing data Use tools and techniques for data visualization and image analysis Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch Who This Book Is For Experienced Python developers who need to learn about Pythonic tools for data analysis
