Free e book to download Python Data Analysis -

Python Data Analysis - Third Edition: Perform data collection, data processing, wrangling, visualization, and more using Python by Avinash Navlani, Armando Fandango, Ivan Idris

• Python Data Analysis - Third Edition: Perform data collection, data processing, wrangling, visualization, and more using Python
• Avinash Navlani, Armando Fandango, Ivan Idris
• Page: 121
• Format: pdf, ePub, mobi, fb2
• ISBN: 9781789955248
• Publisher: Packt Publishing

Python Data Analysis - Third Edition: Perform data collection, data processing, wrangling, visualization, and more using Python

Free e book to download Python Data Analysis - Third Edition: Perform data collection, data processing, wrangling, visualization, and more using Python 9781789955248 (English Edition)

Overview

An end-to-end guide to getting well-versed with data analysis pipelines using machine learning algorithms and techniques Key Features Prepare and clean your data, and use it for exploratory analysis, data manipulation, and wrangling Cover various machine learning methods such as supervised, unsupervised, probabilistic, and bayesian Get to grips with graph processing and sentiment analysis using this practical guide Book Description Data analysis generates value from small and big data by finding new patterns and trends. Python is one of the most popular and easy tools to analyze a variety of data. This book is a handy guide to get well versed with all the phases and methodologies used in the data analysis domain. You will be using modern libraries from the Python ecosystem to create efficient data pipelines. To begin with, you will focus on the essential statistical overview and data analysis fundamentals using Python. You will perform effective and complex data analysis and modeling, data manipulation, data cleaning, data visualization and more using easy-to-follow examples. The book focuses on the practical, relevant fundamentals, in-depth and advanced description of Python data analysis. You will perform time-series analysis and signal processing using ARMA models. Later you will learn to bring smart processing and deep dive into data analytics using machine learning algorithms like regression, classification, PCA, clustering, and more. You will pick real-world examples to analyze textual and image data using NLP and image analytics techniques respectively. Later you will focus on parallel computing using Dask. By the end of this book, you will learn to prepare data for analysis, and create meaningful data visualizations to forecast values from data. What you will learn Learn about data science and its various process model Perform data manipulations such as aggregating, cleaning, and handling missing values using NumPy and Pandas Create interactive visualizations using matplotlib, seaborn and bokeh Retrieve, process and store data in various formats Learn data preprocessing and feature engineering using pandas and scikit-learn Perform time-series and signal processing examples using sunspot cycles data Analyze textual data and image data to perform advanced analysis Learn about parallel computing using Dask. Who This Book Is For This book is for data analysts, business analysts, statisticians, and data scientists who would like to learn and perform end-to-end data analysis using Python. Also, students, academic trainers, and faculty can refer this book to learn and teach with a classic hands-on approach for Python data analysis. This will work as a comprehensive guide to get well versed with various data science methodologies. Some basics of math and working knowledge of Python programming language is expected.

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