Big Data Analysis With Python
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Python Data Analysis
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Author : Avinash Navlani
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-05
Python Data Analysis written by Avinash Navlani and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-05 with Computers categories.
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.
Python Data Analytics
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Author : Stephen Ward
language : en
Publisher:
Release Date : 2020-10-15
Python Data Analytics written by Stephen Ward and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with categories.
Unlock the programming skills you need to prepare for a lucrative career in Data Science with this comprehensive introduction to Python programming for data analytics! Are you completely new to programming and want to learn how to code, but don't know where to begin? Are you looking to upgrade your data wrangling skills to future-proof your career and break into Data Science and Analytics? If you answered yes to any of the questions above, then keep reading... Data analysis has become a huge industry with tons of career potential and will remain relevant far into the foreseeable future. With the exponential growth and explosion of new data and the focus on using data to improve customer experiences and carry out research, data analysts will be needed to process and make sense of large amounts of information, with Python being the language of choice because of its versatility. In this guide, you're going to be shown everything you need to break into the world of Data Analysis with Python. Filled with tutorials for powerful libraries and practical, hands-on exercises, you're going to learn how to aggregate, munge, analyze and visualize data in Python. Here's a sample of what you're going to discover in Python Data Analytics Why Python is the perfect language to learn if you want to break into Big Data and data analytics Core statistical models and computation methods you need to know about as a budding data analyst How to master the CSV library for reading, writing and handling tabular data Using the Xlrd library to extract data from Microsoft Excel files How to convert text to speech using the powerful Win32.com library How to use the NumPy library to carry out fundamental and basic scientific and technical computing How to use the SciPy library to carry out advanced scientific and highly technical computing Surefire ways to manipulate the easy-to-use data structures of the Pandas framework for high-performance data analysis How to plot complex data, create figures and visualize data using the Python Matplotlib library ...and tons more! If you're completely new to programming and have never written a single line of code, but want to get started, this guide is perfect for as a crash guide to getting up to speed with programming in general. Whether you're a programmer looking to switch into an exciting new field with lots of potential for the future, or a regular data analyst looking to acquire the skills needed to remain relevant in a fast-changing world, this guide will teach you how to master powerful libraries used in the real-world by experienced data scientists.
Big Data Analysis With Python
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Author : Ivan Marin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-04-10
Big Data Analysis With Python written by Ivan Marin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Computers categories.
Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python. Key FeaturesGet a hands-on, fast-paced introduction to the Python data science stackExplore ways to create useful metrics and statistics from large datasetsCreate detailed analysis reports with real-world dataBook Description Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools. By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs. What you will learnUse Python to read and transform data into different formatsGenerate basic statistics and metrics using data on diskWork with computing tasks distributed over a clusterConvert data from various sources into storage or querying formatsPrepare data for statistical analysis, visualization, and machine learningPresent data in the form of effective visualsWho this book is for Big Data Analysis with Python is designed for Python developers, data analysts, and data scientists who want to get hands-on with methods to control data and transform it into impactful insights. Basic knowledge of statistical measurements and relational databases will help you to understand various concepts explained in this book.
Python For Data Analysis
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Author : Matt Algore
language : en
Publisher:
Release Date : 2021-01-14
Python For Data Analysis written by Matt Algore and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Computers categories.
Talking about the IT world, there are many options when you have to choose language programming to learn and then to use for developing your career, especially if you want to become a Data Scientist. Python is one of the topmost languages and is becoming more and more popular because of plenty of reasons and one of the key reasons is that it is the best language to master if you want to analyze the data or get into the field of data analysis and data sciences. This Handbook will not only give you reasons on why you need to learn data science, but it will also tell you why learning data science with Python training is the better option. In this book you will: - Have a Clear and Exhaustive Explanation About Data Analysis and Why It Is So Important Today in The Business World; organizations of all sizes rely on the insights they extract from the data they have to measure progress, make informed decisions, plan for the future, and so on. Data scientists are the people who process and organize the data with scientific methods, algorithms, and other techniques. - Understand Why Python is Preferred to Use For Data Analysis Over Other Toolsand the reasons why all the benefits of using Python made it the best tool to learn data science. - Find a Step by Step Process to Install Python on Your Computer and a complete analysis of its hundreds of different libraries and frameworks which is a great addition to your development process. There's one library and framework for every need! - Have a Complete and Exhaustive List of Python Application to realize how this tool is flexible if you want to try something creative that's never done before. Due to that, it's possible to build data models, systematize data sets, create ML-powered algorithms, web services, and apply data mining to accomplish different tasks in a brief time for any kind of business organization - Learn How to Carry Out Work More and More Complex and Difficult to be updated on new themes and trends in the sector and carry out small independent jobs to finance your projects. - & Lot More! Are you completely new to programming and want to learn how to code, but don't know where to begin? Are you looking to upgrade your data wrangling skills to future-proof your career and break into Data Science and Analytics? Python is one of the most valuable and interesting languages for data analysis. Therefore, the popularity of Python is growing day by day, especially in the world of data analysis or data sciences. This Definitive Guide will combine Data Analysis and Python to give you the best information you could find. This guide is perfect to help you build amazing products and help businesses Order Your Copy Now and Start Becoming a Successful Python Expert!
Python For Big Data And Analytics
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Author : THOMPSON. CARTER
language : en
Publisher: Independently Published
Release Date : 2025-01-20
Python For Big Data And Analytics written by THOMPSON. CARTER and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-20 with Computers categories.
Python for Big Data and Analytics: Harness the Power of Python for Processing and Analyzing Large Data Sets Unlock the power of Python for big data with Python for Big Data and Analytics. Designed for data scientists, analysts, and IT professionals, this comprehensive guide takes you step-by-step through the tools, techniques, and best practices for processing and analyzing massive datasets. Whether you're working with structured data, unstructured data, or real-time streams, this book provides the knowledge and practical examples you need to master big data analytics with Python. From foundational concepts to advanced techniques, Python for Big Data and Analytics equips you with the skills to transform raw data into actionable insights. What You'll Learn: Getting Started with Python for Big Data: Understand why Python is the ideal language for big data analytics and set up your development environment. Data Wrangling and Cleaning: Use libraries like pandas and NumPy to clean, transform, and preprocess large datasets efficiently. Big Data Frameworks: Leverage tools like PySpark, Dask, and Ray to process and analyze massive datasets in parallel. Real-Time Data Processing: Work with streaming data using libraries like Apache Kafka and Python-based tools. Exploratory Data Analysis (EDA): Visualize patterns and trends in big datasets with Matplotlib, Seaborn, and Plotly. Machine Learning for Big Data: Build predictive models using scikit-learn, TensorFlow, and PyTorch to analyze and interpret large datasets. Database Integration: Connect Python to big data storage systems like Hadoop, MongoDB, and Amazon Redshift. Cloud Computing for Big Data: Deploy and scale Python-based analytics solutions on AWS, Google Cloud, and Azure. Handling Unstructured Data: Analyze text, images, and other unstructured data formats with libraries like NLTK, spaCy, and OpenCV. Time-Series Analysis: Perform advanced time-series analysis and forecasting on large-scale temporal data. Big Data Visualization: Create interactive dashboards and data visualizations using Bokeh and Dash. Optimizing Performance: Learn best practices for optimizing Python code and reducing memory consumption when working with large datasets. Real-World Applications: Solve real-world problems in industries like healthcare, finance, and e-commerce with practical big data projects. Security and Privacy in Big Data: Understand ethical considerations, data governance, and privacy issues in big data analytics. Who Is This Book For? This book is ideal for data professionals, Python programmers, and anyone looking to develop their expertise in big data analytics and processing. Why Choose This Book? With its focus on practical applications and hands-on projects, Python for Big Data and Analytics bridges the gap between theory and implementation, empowering you to tackle the challenges of big data analytics with confidence. Start harnessing the power of Python for big data today with Python for Big Data and Analytics: Harness the Power of Python for Processing and Analyzing Large Data Sets.
Hands On Exploratory Data Analysis With Python
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Author : Suresh Kumar Mukhiya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-03-27
Hands On Exploratory Data Analysis With Python written by Suresh Kumar Mukhiya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-27 with Computers categories.
Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.
Python For Data Analysis
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Author : Brady Ellison
language : en
Publisher:
Release Date :
Python For Data Analysis written by Brady Ellison and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Ready to learn Data Science through Python language? Python for Data Analysis is a step-by-step guide for beginners and dabblers-alike. This book is designed to offer working knowledge of Python and data science and some of the tools required to apply that knowledge. It’s possible that you have little experience with or knowledge of data analysis and are interested in it. You might have some experience in coding. You may have worked with data before and want to use Python. We have made this book in a way that will be helpful to all these groups and more besides in varying ways. This can serve as an introduction to the most current tools and functions of those tools used by data scientists. In this book You will learn: Data Science/Analysis and its applications IPython and Jupyter - an introduction to the basic tools and how to navigate and use them. You will also learn about its importance in a data scientist’s ecosystem. Pandas - a powerful data management Python library that lets you do interesting things with data. You will learn all the basics you need to get started. NumPy - a powerful numerical library for Python. You will learn more about its advantages. Get your copy now
Python For Data Analysis
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Author : Wes McKinney
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-09-25
Python For Data Analysis written by Wes McKinney and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-25 with Computers categories.
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Python Programming
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Author : Computer Science Academy
language : en
Publisher: Giale Limited
Release Date : 2020-11-15
Python Programming written by Computer Science Academy and has been published by Giale Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-15 with Computers categories.
Are you looking to master the fundamental concepts of Data Analysis and Data Science? Do you want learn Python programming language fast? You are in the right place! Python can be used for a variety of coding projects including machine learning algorithms, web applications, data mining and visualization, game development. Some of the highlights of this book include: - What the Python language is - How we can benefit from data analysis, no matter what industry we are. - How Python is able to work well with the data analysis - How to install and use the NumPy library, one of the best extensions with Python, to help us get our data analysis done. - How to work with the Pandas and IPython extensions so that we are able to get things done with your analysis. - A look at the Matplotlib library to help you create some of your own visuals with your data when the analysis is done. - How to work with data visuals and how they are so important to your work. - The five major stages of the TDSP lifecycle. - Installation instructions for Python - Python coding concepts such as data types, classes, and objects variables, numbers, constructor functions, Booleans and much more. - Learn the functioning of various data science libraries like Scikit-Learn - How to create various graphs using Matplotlib and Pandas library. - Learn how machine learning allows analysis of large volumes of data and delivers faster and more accurate results. - Overview of four different machine-learning algorithms - Learn how companies are able to employ a predictive analytics model Even if you have never studied Python language before, you can learn it quickly. So what are you waiting for? Go to the top of the page and click Buy Now!
Data Analytics With Python
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Author : Frank Millstein
language : en
Publisher: Frank Millstein
Release Date : 2020-05-08
Data Analytics With Python written by Frank Millstein and has been published by Frank Millstein this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.
Data Analytics With Python Data is the foundation of this digital age that we live in. With this book, you are going to learn how to organize and analyze data and how to interpret vast sources of information. This book covers various topics on data analytics such as data analytics applications, data analytics process, using Python for data analytics, Python libraries for data analytics and many other that will help you kick-start your data analytics journey from the very beginning. In this book you are going to learn how to use Python its tools in order to interpret data and examine those interesting data trends and information, which are important in predicting the future. Whether you are dealing with some medical data, sales data, web page data, you can use Python in order to interpret data, analyze it and obtain this valuable information. You can also use this data for creating data analytics models and predictions. Here Is A Brief Preview of What You’ll Learn In This Book… -Data analytics applications -Data analytics process -How to install and run Python -Python data structures and Python libraries -Python conditional construct and iteration -Data exploration using Pandas -Pandas series and dataframes -Data munging and distribution analysis -Carrying out binary operations -Data manipulation and categorical variable analysis -How to build a predictive model -And of course much, much more! Get this book NOW and learn more about Data Analytics With Python!