Download or read book Ultimate Python Libraries for Data Analysis and Visualization written by Abhinaba Banerjee and published by Orange Education Pvt Ltd. This book was released on 2024-04-04 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Test your Data Analysis skills to its fullest using Python and other no-code tools KEY FEATURES ● Comprehensive coverage of Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, Julius AI for data acquisition, preparation, analysis, and visualization ● Real-world projects and practical applications for hands-on learning ● In-depth exploration of low-code and no-code tools for enhanced productivity DESCRIPTION Ultimate Data Analysis and Visualization with Python is your comprehensive guide to mastering the intricacies of data analysis and visualization using Python. This book serves as your roadmap to unlocking the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI. Starting with the fundamentals of data acquisition, you'll learn essential techniques for gathering and preparing data for analysis. From there, you’ll dive into exploratory data analysis, uncovering patterns and relationships hidden within your datasets. Through step-by-step tutorials, you'll gain proficiency in statistical analysis, time series forecasting, and signal processing, equipping you with the tools to extract actionable insights from any dataset. What sets this book apart is its emphasis on real-world applications. With a series of hands-on projects, you’ll apply your newfound skills to analyze diverse datasets spanning industries such as finance, healthcare, e-commerce, and more. By the end of the book, you'll have the confidence and expertise to tackle any data analysis challenge with Python. To aid your journey, the book includes a handy Python cheat sheet in the appendix, serving as a quick reference guide for common functions and syntax. WHAT WILL YOU LEARN ● Acquire data from various sources using Python, including web scraping, APIs, and databases. ● Clean and prepare datasets for analysis, handling missing values, outliers, and inconsistencies. ● Conduct exploratory data analysis to uncover patterns, trends, and relationships within your data. ● Perform statistical analysis using Python libraries such as NumPy and Pandas, including hypothesis testing and regression analysis. ● Master time series analysis techniques for forecasting future trends and making data-driven decisions. ● Apply signal processing methods to analyze and interpret signals in data, such as audio, image, and sensor data. ● Engage in real-world projects across diverse industries, from finance to healthcare, to reinforce your skills and experience. ● Utilize Python for in-depth analysis of real-world datasets, gaining practical experience and insights. ● Refer to the Python cheat sheet in the appendix for quick access to common functions and syntax, aiding your learning and development. WHO IS THIS BOOK FOR? This book is ideal for beginners, professionals, or students aiming to enhance their careers through hands-on experience in data acquisition, preparation, analysis, time series, and signal processing. Prerequisite knowledge includes basic Python and introductory statistics. Whether starting fresh or seeking to refresh skills, this comprehensive guide helps readers upskill effectively. TABLE OF CONTENTS 1. Introduction to Data Analysis and Data Visualization using Python 2. Data Acquisition 3. Data Cleaning and Preparation 4. Exploratory Data Analysis 5. Statistical Analysis 6. Time Series Analysis and Forecasting 7. Signal Processing 8. Analyzing Real-World Data Sets using Python APPENDIX A Python Cheat Sheet Index

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!

Download or read book Python For Data Science written by Mark Graph and published by . This book was released on 2019-12-10 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives you the perfect foray into data analysis. We discuss data analysis in Python in a way that will benefit you irrespective of your expertise level in Python. At the beginner level, you will appreciate the simple but elaborate approach we use to introduce you to basic Python concepts necessary for data analysis. With this knowledge, you can establish your foundation in data analysis, and build on that over time as you become accustomed to more complex subjects. For intermediate and expert users, you can also benefit from this book by using it as a reminder of some of the key points that define data science. When you dwell in a field for a long time, it is easy to take some things for granted. This happens to many programmers and developers. This book reminds you of the basic building principles that have helped you become one of the best data analysts in your field. Python libraries are some of the most important features in Python programming. The libraries help you perform tasks that would have otherwise been impossible to perform, or cumbersome. We discuss the major Python libraries you will use all the time, and highlight the main ones relevant to data analysis so you can get the distinction. Take note that data science is not an isolated subject. Most of the disciplines that involve Python programming depend on data, so you can expect to use the knowledge learned in this book in other fields, too. For example, when you advance into machine learning, your ability to perform exceptional data analysis will be required to help you build and train relevant machine learning models. Therefore, this book will not just get you ready for data analysis, it will prepare you for various fields in Python programming, including artificial intelligence, deep learning, and machine learning. Besides discussing the main Python libraries, we investigate the major data analysis libraries like Pandas and Matplotlib in-depth. These libraries will form the foundation of most of the data analysis work you perform over the years. Data analysis in Python will help you become an all-rounded developer. The good thing about learning Python is that you can use the knowledge gained to further your career in other programming languages like R. It is important to learn Python for data analysis from a conceptual and fundamental framework so that you set the right tone on which you can build your career further and advance into the future. Unlike other books, I don't claim that this book will make you a master of data science after a single read. That's not realistic, in fact, it's even a bit absurd. What I claim is that you will definitely learn about the basics. The rest is practice. The more you practice the better you code.

Download or read book Python for Data Analysis written by Matt Foster and published by . This book was released on 2020-01-05 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the Python Programming Language and Data Analysis With This Comprehensive Guide! If you would like to... Grow your business Get an amazing job Make great business decisions Get rid of the competition... This book will teach you how to achieve all that with the help of data analysis and data science. It might sound like a lot of work, but with proper guidance, you don't need to spend hours bent over textbooks and trying to make sense of a huge amount of information. The goal of this book is not only to learn about data analysis but to go from this theoretical to practical knowledge and application. In other words, you'll be able to complete your own analysis, implement its methods in your business, and master the Python Programming Language! Here's what you'll learn with this book: The importance of data analysis and why every successful business and industry are using it How to process data with tools and techniques used by data scientists The concepts behind Python programming How to use the "data munging" process How to use Python libraries such as Pandas and NumPy for data analysis The importance of data visualization How to create the right analytical algorithm for predicting the market trends How to write codes, and create programs and databases And much more! Even if this is the first time you're hearing about Data Analysis and Python, you can still successfully learn everything this book offers. The instructions are incredibly simple, the methods explained to the finest details and the guides are presented in a step-by-step way. You don't have to be a computer or math expert to develop this skill. You simply need a straightforward guide on the steps you have to take, with clear background explanations to help you understand those steps. If you want to modernize your company and your skills, make the most of your data and become a competitive force on the market, Scroll up, click on "Buy Now with 1-Click", and Get Your Copy Now!

Download or read book Python Data Analytics written by Ethan Williams and published by . This book was released on 2019-08-16 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: IntroductionHave 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 learningIf 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. This is precisely what makes Python an ideal tool for beginners. It is open sourceThis 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. There are so many open-source python libraries such as Data manipulation, statistics, visualization, machine learning, mathematics, and natural language processing, among others.It is well-supportedDid 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!The most fortunate thing with Python is that it is widely used both in academics and industrial levels. This means that there are so many analytical libraries at your disposal. Therefore, if as a python user, you get stuck and need help, you can get it quickly on Stack Overflow's user-contributed codes, mailing lists, and documentation. The more python gains popularity, the more the users keep contributing information on their experience with the programming language. That said, one thing that is important to note is that Python is not an overly complicated language to use. The price is right and all the support you need out there to ensure that while working on your project, you do not come to a screeching halt whenever you hit a snag.

Download or read book Ultimate Python for Fintech Solutions written by Bhagvan Kommadi and published by Orange Education Pvt Ltd. This book was released on 2024-07-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: TAGLINE Creating Next Gen Apps in Finance KEY FEATURES ● Master the Python libraries and packages essential for financial applications, enabling robust development. ● Utilize Python for developing applications that process financial information, visualize data in diverse formats, and create insightful representations. ● Derive analytical insights from mathematical models integrated into Python applications for data-driven decision-making in finance and fintech. DESCRIPTION Dive into the dynamic world where finance meets fintech with Python's versatile capabilities in this 'Ultimate Python for Fintech Solutions'. Whether you're aiming to build secure trading platforms, conduct deep statistical analysis, or pioneer next-generation financial technologies, this book quips you with the knowledge, tools, and practical insights to succeed. This book starts with Python's foundational programming techniques, essential for understanding financial principles and laying the groundwork for robust applications. You will learn to build scalable solutions that handle complex financial data with ease by using Python for analysis, forecasting, and data visualization. Next, it moves to explore advanced topics like AI/ML applications tailored for finance, enabling you to unlock predictive insights and streamline decision-making processes. You will discover how Python integrates cutting-edge technologies such as Big Data and Blockchain, to offer innovative solutions for modern fintech challenges. By the end of this expansive book, you will gain the expertise needed to develop sophisticated financial applications, visualize data effectively across desktop and web platforms, and drive innovation in fintech. WHAT WILL YOU LEARN ● Learn to build robust applications tailored for financial analysis, modeling, and fintech solutions using Python. ● Learn to analyze large volumes of financial data, and visualize insights effectively. ● Apply advanced AI/ML techniques to predict trends, optimize financial strategies, and automate decision-making processes. ● Integrate Python with Big Data platforms and Blockchain technologies to work with massive datasets and decentralized financial systems. ● Acquire the knowledge and skills to innovate in the fintech space to address modern financial challenges and opportunities. WHO IS THIS BOOK FOR? This book is for working professionals, students, business managers, consultants, technical/functional analysts, anyone wishing to improve their skills in Fintech with Python. This book will be a great start for a programmer who wants to start on the Python tech stack and make a career in Fintech space. The prerequisites for the reader will be basic mathematics and advanced math topics such as time series, derivatives, and integrals. The outcome for the reader will be to understand mathematical modeling and to have capability to develop next gen financial apps. TABLE OF CONTENTS 1. Getting Started on Python Infrastructure and Building Financial Apps 2. Learning Financial Concepts Using Python 3. Data Structures and Algorithms Using Python 4. Object Oriented Programming Using Python 5. Building Simulation and Mathematical Analysis Tools Using Python 6. Stochastic Mathematics and Building Models Using Python 7. Prediction Algorithms Using Python 8. Data Science and Statistical Algorithms Using Python 9. Desktop and Web Charting Using Python 10. AI/ML Apps Using Python 11. Big Data/Blockchain-Based Solutions Using Python 12. Next Generation FinTech Apps Using Python with Financial Singularity Index

Download or read book Python for Data Analysis written by Guido Van Smit and published by . This book was released on 2019-11-27 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in PythonPython for Data Analysis represents now one of the most interesting and useful applications among all the possible applications of Machine Learning and Artificial Intelligence. This guidebook is the ultimate guide to learning insights and strategies to help you grow your business, save time, resources, and energy or if you are looking for a new job, but it requires a solid background in terms of processes and technologies involved. It will walk you through the entire program from A to Z and offers a straightforward approach to Python with plenty of opportunities for hands-on learning and improving your skills. Inside, you'll find: What is and how Data Analysis works Essentials Python Libraries: NumPy, Pandas, IPython and Jupyter Data Types in Python Text Analysis in Python 3 Analyze and manipulate regular and irregular time series data Practical applications to put into use today And so much more! Installation and Setup If you're ready to fully grasp Python for Data Analysis, this book is the perfect guide to help you!

Download or read book Python for Data Analysis written by Daniel Howard and published by . This book was released on 2019-11-24 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you searching for a professional guide for learning data analysis from scratch? In this crash course, you will find everything you need to become proficient in this discipline, regardless of your previous experience. Starting from the basics, Daniel Howard will teach you the most up-to-date techniques to manipulate and process data, using Python libraries such us NumPy, Pandas and Matplotlib. Python is one of the most famous programming languages and it is recognized as the most effective tool for machine learning and data science, thanks to its large number of dedicated resources. Since it is designed for everyone, you will be amazed by the large number of programs that you will be able to create in no time, even as a beginner. Here is a preview of what you will learn: What data analysis is, and why it is fundamental in hundreds of business and technological applications Effective computational methods to manipulate large amounts of data Data visualization tools and techniques How to develop a successful career in one of the best paid sectors Real-world applications of machine learning and artificial intelligence What predictive modeling is How to build neural networks with Python If you are a student or a professional looking for more technical skills, or if you are simply curious about data analytics and its powerful applications, then click the BUY button and get your copy!

Download or read book Ultimate Enterprise Data Analysis and Forecasting using Python written by Shanthababu Pandian and published by Orange Education Pvt Ltd. This book was released on 2023-12-28 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Approaches to Time Series Analysis and Forecasting using Python for Informed Decision-Making KEY FEATURES ● Comprehensive Resource for Python-Based Time Series Analysis and Forecasting. ● Delve into real-world applications with industry-specific case studies. ● Extract valuable insights by solving time series challenges across various sectors. ● Understand the significance of Azure Time Series Insights and AWS Forecast components. ● Practical insights into leveraging cloud platforms for efficient time series forecasting. DESCRIPTION Embark on a transformative journey through the intricacies of time series analysis and forecasting with this comprehensive handbook. Beginning with the essential packages for data science and machine learning projects you will delve into Python's prowess for efficient time series data analysis, exploring the core components and real-world applications across various industries through compelling use-case studies. From understanding classical models like AR, MA, ARMA, and ARIMA to exploring advanced techniques such as exponential smoothing and ETS methods, this guide ensures a deep understanding of the subject. It will help you navigate the complexities of vector autoregression (VAR, VMA, VARMA) and elevate your skills with a deep dive into deep learning techniques for time series analysis. By the end of this book, you will be able to harness the capabilities of Azure Time Series Insights and explore the cutting-edge AWS Forecast components, unlocking the cloud's power for advanced and scalable time series forecasting. WHAT WILL YOU LEARN ● Explore Time Series Data Analysis and Forecasting, covering components and significance. ● Gain a practical understanding through hands-on examples and real-world case studies. ● Master Time Series Models (AR, MA, ARMA, ARIMA, VAR, VMA, VARMA) with executable samples. ● Delve into Deep Learning for Time Series Analysis, demystified with classical examples. ● Actively engage with Azure Time Series Insights and AWS Forecast components for a contemporary perspective. WHO IS THIS BOOK FOR? This book caters to beginners, intermediates, and practitioners in data-related fields such as Data Analysts, Data Scientists, and Machine Learning Engineers, as well as those venturing into Time Series Analysis and Forecasting. It assumes readers have a foundational understanding of programming languages (C, C++, Python), data structures, statistics, and visualization concepts. With a focus on specific projects, it also functions as a quick reference for advanced users. TABLE OF CONTENTS 1. Introduction to Python and its key packages for DS and ML Projects 2. Python for Time Series Data Analysis 3. Time Series Analysis and its Components 4. Time Series Analysis and Forecasting Opportunities in Various Industries 5. Exploring various aspects of Time Series Analysis and Forecasting 6. Exploring Time Series Models - AR, MA, ARMA, and ARIMA 7. Understanding Exponential Smoothing and ETS Methods in TSA 8. Exploring Vector Autoregression and its Subsets (VAR, VMA, and VARMA) 9. Deep Learning for Time Series Analysis and Forecasting 10. Azure Time Series Insights 11. AWSForecast Index

Download or read book Ultimate Pandas for Data Manipulation and Visualization written by Tahera Firdose and published by Orange Education Pvt Ltd. This book was released on 2024-06-10 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: TAGLINE Unlock the power of Data Manipulation with Pandas. KEY FEATURES ● Master Pandas from basics to advanced and its data manipulation techniques. ● Visualize data effectively with Matplotlib and explore data efficiently. ● Learn through hands-on examples and practical real-world use cases. DESCRIPTION Unlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. WHAT WILL YOU LEARN ● Wrangle data efficiently using Pandas' cleaning, filtering, and transformation techniques. ● Unlock hidden patterns with advanced grouping, joining, and merging operations. ● Master time series analysis with Pandas to extract valuable insights from your data. ● Apply Pandas to real-world scenarios like customer churn analysis and financial modeling. ● Unleash the power of data visualization with Matplotlib and craft compelling charts and graphs. ● Enhance your workflow with essential Pandas optimizations and performance tips. WHO IS THIS BOOK FOR? This book is ideal for aspiring data scientists, analysts, and Python enthusiasts looking to enhance their data manipulation skills using Pandas. Familiarity with Python programming basics and a basic understanding of data structures will greatly benefit readers as they delve into the concepts presented in this book. TABLE OF CONTENTS 1. Introduction to Pandas and Data Analysis 2. Pandas Series 3. Pandas DataFrame 4. Data Cleaning with Pandas 5. Data Filtering with Pandas 6. Grouping and Aggregating Data 7. Reshaping and Pivoting in Pandas 8. Joining and Merging Data in Pandas 9. Introduction to Time Series Analysis in Pandas 10. Visualization Using Matplotlib 11. Analyzing Bank Customer Churn Using Pandas Index

Download or read book Python Data Analytics written by Stephen Ward and published by . This book was released on 2020-10-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Python Data Science written by Jessica Rizzo and published by . This book was released on 2019-08-25 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're tired of licensing third-party software for data analysis, Python Data Science will help you do it for yourself! Recently, more and more companies are learning that they need to make DATA-DRIVEN decisions. And with big data and data science on the rise, we now have more data than we know what to do with. In fact, without a doubt, you have already experienced data science in one way or another. Obviously, you are interacting with data science products every time you search for information on the web by using search engines such as Google, or asking for directions with your mobile phone. Data science is the science and technology focused on collecting raw data and processing it in an effective manner. It is the combination of concepts and methods that make it possible to give meaning and understandability to huge volumes of data. Data science has been the force behind resolving some of our most common daily tasks for several years. In nearly all of our daily work, we directly or indirectly work on storing and exchanging data. With the rapid development of technology, the need to store data effectively is also increasing. That's why it needs to be handled properly. Basically, data science unearths the hidden insights of raw-data and uses them for productive output. Python is often used in data science today because it is a mature programming language that has excellent properties for newbie programmers. Some of the most remarkable of these properties are its easy to read code, suppression of non-mandatory delimiters, dynamic typing, and dynamic memory usage. Python is an interpreted language, and it can be executed in the Python console without any need to compile to machine language. "Python Data Science" teaches a complete course of data science, including key topics like data integration, data mining, python etc. We will explore NumPy for numerical data, Pandas for data analysis, IPython, Scikit-learn and Tensorflow for machine learning and business. Each of the chapters in this book is devoted to one of the most interesting aspects of data analysis and processing. The following are some of the major topics covered in Python Data Science: Understanding Data Science Getting Started with Python for Data Scientists Descriptive statistics Data Analysis and Libraries NumPy Arrays and Vectorized Computation Data Analysis with Pandas Data Visualization Data Mining Classifying with Scikit-learn Estimators Giving Computers the Ability to Learn from Data Training Machine Learning Algorithms The Python ecosystem for data science discussed within Python Data Science includes SciPy, NumPy, Matplotlib, Pandas, and Scikit-learn, which provides all of the data science algorithms. Data processing and analysis is one of the hottest areas of IT, where developers who can handle projects of any level, from social networks to trained systems, are constantly required. We hope this book will be the starting point for your journey into the fascinating world of Data Science. To get started on your Python adventure, just scroll back up and click the 'Buy' button.

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 565 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.

Download or read book Data Science with Python written by Julian James McKinnon and published by DM Publishing. This book was released on 2020-11-08 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis is just getting started. There's no limit to the amount of data available and more companies are now interested in data analysis. For you, it's important to understand the concepts of data analysis and then, through practice, build a good command on working with different datasets. If you are feeling confident enough after finishing this book, you can move towards data science. It's much more complex, contains more abstract concepts, there's more mathematics involved, and it's easier to get lost. The more difficult the field, the higher the rewards. That's why data science is one of the most promising careers today. Data science is a role that is taking up a lot of space for many businesses. There is a wealth of information out there that they are able to use for their own advantage, but they just need to know where to gather it, and how to analyze all of that data for their own needs. Sometimes, this is going to be a process that takes a lot of time and effort and can be hard to keep up with and ensure that we are doing it in the right manner. Data science is the process of gathering, organizing and cleaning, analyzing, and then visualizing data so that we can use that information to make smart business decisions. It is becoming more and more important to a lot of businesses, and it is likely that this will take over as one of the main forms of making big decisions in the future. With that in mind, let's take some time to look more in-depth at data science and how businesses are using it for their own needs. Many businesses, no matter what kind of industry they conduct business in, will find that working with data science is one of the best options for them. Data science can help them to really learn about their industry, and even gain a leg up on the competition. Many of the companies out there are going to already collect a lot of data and information about things like the competition, the industry, and their customers, and data science is going to help them to see what insights and information are inside of that data and use it for their advantage. There are many times when bringing out data science is going to be beneficial, and it will be able to propel your business forward more than anything else can do. When we can focus on the data and the process of analyzing it and seeing what good insights and predictions are inside, we will be able to make accurate decisions that will help us to make a big difference. Companies who have been able to implement a successful data science project from beginning to end are the ones who are doing the best overall in their respective industries. This book gives a comprehensive guide on the following: What is data science? Basics of python The best python libraries for data science Data science and applications The lifecycle of data science Probability, statistics and data types Most common data science problems Comparison of python with other languages Data cleaning and preparation Data visualization ... AND MORE!!!

Download or read book Data Science with Python written by Julian James McKinnon and published by . This book was released on 2020-02-10 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis is just getting started. There's no limit to the amount of data available and more companies are now interested in data analysis. For you, it's important to understand the concepts of data analysis and then, through practice, build a good command on working with different datasets. If you are feeling confident enough after finishing this book, you can move towards data science. It's much more complex, contains more abstract concepts, there's more mathematics involved, and it's easier to get lost. The more difficult the field, the higher the rewards. That's why data science is one of the most promising careers today. Data science is a role that is taking up a lot of space for many businesses. There is a wealth of information out there that they are able to use for their own advantage, but they just need to know where to gather it, and how to analyze all of that data for their own needs. Sometimes, this is going to be a process that takes a lot of time and effort and can be hard to keep up with and ensure that we are doing it in the right manner. Data science is the process of gathering, organizing and cleaning, analyzing, and then visualizing data so that we can use that information to make smart business decisions. It is becoming more and more important to a lot of businesses, and it is likely that this will take over as one of the main forms of making big decisions in the future. With that in mind, let's take some time to look more in-depth at data science and how businesses are using it for their own needs. Many businesses, no matter what kind of industry they conduct business in, will find that working with data science is one of the best options for them. Data science can help them to really learn about their industry, and even gain a leg up on the competition. Many of the companies out there are going to already collect a lot of data and information about things like the competition, the industry, and their customers, and data science is going to help them to see what insights and information are inside of that data and use it for their advantage. There are many times when bringing out data science is going to be beneficial, and it will be able to propel your business forward more than anything else can do. When we can focus on the data and the process of analyzing it and seeing what good insights and predictions are inside, we will be able to make accurate decisions that will help us to make a big difference. Companies who have been able to implement a successful data science project from beginning to end are the ones who are doing the best overall in their respective industries. This book gives a comprehensive guide on the following: What is data science? Basics of python The best python libraries for data science Data science and applications The lifecycle of data science Probability, statistics and data types Most common data science problems Comparison of python with other languages Data cleaning and preparation Data visualization ... AND MORE!!! Buy your copy of the book now and enjoy more content. What are you waiting for?Scroll Up and Click the Buy Now Button!

Download or read book Python For Data Analysis written by Matt Algore and published by . This book was released on 2021-01-06 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Tools and 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!

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.