Data Analysis Books that You Can Buy

Statistics are used R language to analyze data and nowadays the popularity of this language is increasing day by day. IoT is able to gather lots amount of data which helps to gain practical insights by analyzing data.

This book will help you to learn:

• People who are interested in graphic visualization can get help from this book and achieve their desired data analysis.
• You will also get the idea of storing and manipulating data by creating matrices and helping to plot graphs for better understanding.
• Also explains the core of the language and also the principle of R language.
• It is organized with separate chapters for different features of the R language.
• It helps to learn about different graphs and charts like Bar charts, Line charts, Scatter graphs, Box plots, etc.

This book is about practical case studies which will help you to solve problems effectively.

This book will help you to learn:

• The latest version of NumPy, Pandas, Jupiter.
• How to use the tools and start data analysis using the panda's library.
• Creating informative visualizations with the help of matplotlib Transforming, merging, and reshaping data by using tools.
• Analyzing the regularity and irregularity of time series data.

This third edition of the book summarizes the methods and processes of using the software.

This book will help you to learn:

• How to use for software of R language and performance of the analysis.
• The introduction of Bayesian approaches in new sections in many chapters of this book.
• The short solutions of this book will help to learn the process of SAS, Stata & SPSS.
• This book also helps to use the writing methods of applied and nontechnical styles.

Data Analysis presents the comparison and frameworks that can apply for modeling which includes the predictor of products.

This third edition of this book is reflecting:

• The logistics regression by adding new sections in this book.
• Examples with updated information.
• A clear conception of this topic by using PowerPoint, tools, and websites.
• The researches with a different problem set like data sets, R code, test questions, and many more.

This book is a qualitative guide on Data Analysis for the students. This book is about designing, coding, comparison, cases & so on.

You will also learn from this book:

• The rules of using NVivo on pc & MacBook.
• Also about the screenshots & clicking guidance.
• The easy following steps for interweaves theory.
• Enhancing the learning capability of the students by critical thinking.

The practical knowledge of Data Analysis with pandas will show you how to work effectively & the primary starting point of Machine Learning. This book will help you to know using of the panda's library for real datasets. Also cleaning and .aggregating your data.

This book will also help you to learn:

• What kind of rules are followed by the data analysts or scientists for gathering data.
• Use of Python for data wrangling and analyzing.
• Use of Machine Learning algorithms for identifying the patterns and predictions.
• Use of pandas for representing data.

According to the variety, velocity & volume analysts are classified data. Use of the pandas library and Python any type of complex dataset can be solved. This book is all about practical knowledge of problem-solving which is also understandable for new data analysts.

Also, You will learn:

• How to be worked with Data Frames.
• Implementation of matplotlib, pandas &seaborn.
• How to make clean, reshaping, and easygoing datasets.
• Conversion of data.
• Comparison of multiple data for choosing the best one.

With the case study, this book is organized to learn statical analysis. Here is also the process of data analysis. Through this book you will also learn:

• How to write and test code for better understanding & development of probability and statistics.
• How to run the experiments.
• How to solve the real-world data using statistical interference.

This book gives instructions on how to get data from a relational database.

Through this book you will also learn:

• Using of tools for data analysis and query.
• Learning the techniques for working with SQL & Excel.
• Designing the data analysis by using SQL.

In this edition, this book explains how to work with complex datasets.

You will also learn:

• Connecting with different data sources: JSON, CSV, Avro, etc.
• Building data pipelines with reliability.
• Debugging spark operation.