Learn Data Analysis With Python
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Learn Data Analysis with Python
Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it. Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects. If you aren’t using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished. What You Will Learn Get data into and out of Python code Prepare the data and its format Find the meaning of the data Visualize the data using iPython Who This Book Is For Those who want to learn data analysis using Python. Some experience with Python is recommended but not required, as is some prior experience with data analysis or data science.
Python For Data Analysis
Do you Want to learn more about Python Data Analysis ?.... then read on. Businesses, governments, and organizations all need data for some reason. Data today is an opportunity to understand their current situation and use it to prepare for the unknown. The techniques used in data analysis today are easily available to anyone to interpret the data and obtain relevant explanations. Data analysis requires a detailed understanding of the operation of the computers, peripherals, and software in question. The objective is to give the reader the knowledge necessary to familiarize themselves with the Python language by orienting the problem so as to focus on the functioning of these objects. This book was written with the desire to be accessible to everyone and the conviction that a "democratization" of the understanding of the computer tool is now essential. This book offers a detailed approach: it begins with an introduction to the Python language and then presents how to use it to retrieve and manipulate the data produced by our computers. The authors thus deal with various themes ranging from the inspection of the process RAM, to the internal functioning of mainstream software or to the extraction of web browser history. Different tools are studied: from the most basic to the most recent technologies such as machine learning with scikit-learn and its ecosystem resulting from scientific computing.ompiles (if there is no updated bytecode on disk), and runs on the Python virtual machine. With Python for Data Analysis you'll learn step by step how to implement data analysis and procedures to extract data correctly. In this you also will learning: what's Data Analysis Python For Data Analysis Data Aggregation Application Of Data Analytic today Mathematics For data Analysis Data Wrangling Scipy, Numpy, Panda While most books focus on advanced predictive models, this book begins to explain the basic concepts and how to correctly implement Data Analysis and Data Visualization, with practical examples and simple coding scripts. This guide provides the necessary knowledge in a practical way. You will learn the steps of Data Analysis, how to implement them in Python, and the most important applications in the real world. Download the eBook, Python For Data Analysis. Scroll to the top of the page and click the "Buy now" button to get your copy now.
Python Data Analysis
Author: Avinash Navlani
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-02-05
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.