Hands On Data Analysis with Pandas Book [PDF] Download

Download the fantastic book titled Hands On Data Analysis with Pandas written by Stefanie Molin, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Hands On Data Analysis with Pandas", which was released on 26 July 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Hands On Data Analysis with Pandas by Stefanie Molin PDF

Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.


Detail About Hands On Data Analysis with Pandas PDF

  • Author : Stefanie Molin
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 702 pages
  • ISBN : 1789612802
  • PDF File Size : 7,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Hands-On Data Analysis with Pandas

Hands-On Data Analysis with Pandas
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  • File Size : 47,6 Mb
  • Release Date : 26 July 2019
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Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different

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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

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  • File Size : 39,5 Mb
  • Release Date : 31 July 2017
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This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book