A man can lead a horse to the water but he cannot make him drink. The following two books are required reading for the introduction of data analysis, and also to test whether you really like data analysis.
From 0 to 1: Simple data analysis
Why? To borrow a reader's comment, "All my cats like this book!"
0 1 Introduction
In a vivid form similar to "Zhang Hui's novels", vividly show readers the skills that excellent data analysts should know and understand; After the text, ten important tasks of data analysis, R tools and ToolPak tools are introduced with three appendices, which not only fully display the target knowledge, but also build a bridge for readers to further study.
02 reasons for recommendation
The title of the book has well demonstrated the advantages of this book-"easy to understand". Forget about your troubles. This book interacts closely with the real world, making you not only boring theories, but also simplified knowledge and complex concepts.
Classic little yellow book: "Who says a rookie can't analyze data"
It is a good book, but it is really worthless after reading it.
0 1 Introduction
Many people flinch when they see data analysis, fearing that the threshold is high and they cannot enter the threshold of data analysis. Who says a rookie can't analyze data strives to make data analysis as easy to understand as a novel, so that readers can learn data analysis invisibly and explain it according to the complete process of data analysis.
02 reasons for recommendation
Introduction to data analysis is the best, but it is really an introduction, with advantages and disadvantages. It is an excellent choice for introductory understanding, but it is not enough for later practice. I suggest that students who have been groping for data analysis before go and have a look, which is quite enlightening.
Analysis tool class
There are many tools related to data analysis, such as Excel, PPT and SQL. If you want to master them, you can directly search for a sea of clouds to find relevant quality courses.
1. Good at it
Everyone often says Excel, but don't think you are good at Excel! Excel is a necessary office software for all professionals. Excel is very powerful When the amount of data is not very large, data analysis can basically be realized by Excel. Recommend the following books:
Efficient Office Data Processing and Analysis
0 1 Introduction
According to the main characteristics of modern enterprise decision-making and management, this paper introduces the concrete application of Excel's powerful data processing and analysis function in enterprise decision-making and management.
02 reasons for recommendation
At the same time, this book provides a lot of examples you need to do. There is no learning without practicing!
Don't be afraid, the Excel function is actually very simple.
0 1 Introduction
"Don't be afraid, Excel functions are actually very simple" introduces the calculation principles and application skills of some functions commonly used in Excel with easy-to-understand pictures and texts, vivid metaphors and a large number of classic cases in practical work, and also introduces the scientific management methods of data to avoid problems from the source of data.
02 reasons for recommendation
Suitable for professionals who want to improve office efficiency, especially those who often need to process and analyze a large amount of data and make statistical reports, as well as college teachers and students of related majors, Xiaobai needs to be cautious!
2. Structured query language
SQL is the basis of data analysis, and learning the ability of data analysis is a necessary skill. Then I will only introduce three books to you here. The first book is an introduction to zero foundation, the second is advanced, and the third is a dictionary of SQL. Not much to say, let's go directly to the shelves.
Basic SQL course
0 1 reasons for recommendation
This paper introduces relational database and the usage of SQL language for operating relational database. Through rich illustrations, a large number of sample programs and detailed operation steps, the book enables readers to gradually master the basic knowledge and skills of SQL and effectively improve their programming ability. There are exercises at the end of each chapter to help readers test their understanding of each chapter. In addition, this book also summarizes important knowledge points as "rules" for readers' reference at any time.
This book has 107 charts +209 codes +88 rules, which is a must for zero-based advanced learners!
Advanced SQL: advanced SQL tutorial
0 1 reasons for recommendation
This book is a guide for intermediate and advanced database engineers to improve their SQL skills. This book can be divided into two parts. The first part introduces the special skills of using SQL language and leads readers to explore the new discoveries of common SQL technologies. Designed to help readers improve their programming level; The second part focuses on the development history of relational database, combining practice with theory, aiming to help readers deepen their understanding of relational database and SQL language.
This book is not suitable for Xiao Bai! Suitable for readers who have more than half a year's experience in using SQL, have mastered the basic knowledge and skills of SQL and want to improve their programming level.
SQL tutorial books
0 1 reasons for recommendation
This book is a reference textbook for MIT, University of Illinois and many other universities. It explains the contents of SQL from the simple to the deep, with rich examples and easy reference. This book does not elaborate the basic theory of database too much, but focuses on the front-line software developers and directly starts with SQL SELECT, telling the most commonly used and needed SQL knowledge in the actual working environment, which is very practical.
People with a certain SQL foundation can use it as a dictionary, and they can find the corresponding internal use when they encounter problems.
3. Computer programming language
Life is short, I use Python. Python programming language is the simplest and most powerful language. But many people claim to be proficient in Python, but they can't write Python code themselves, and they don't know much about many commonly used packages. From the beginning, let's start with the most basic in Python.
Python programming, from introduction to practice
0 1 reasons for recommendation
The biggest feature of this book is that even a little white who doesn't know programming at all can learn it, and beginners can't go wrong if they want to learn it. Knowledge points are gradually followed up from shallow to deep, and there are video tutorials to teach them by hand. At the same time, the required software is also free. This book is also accompanied by relevant counseling books. You can read it if you are interested, but please remember that this book is the core.
Using Python for data analysis
0 1 reasons for recommendation
Unlike other programming books, it started with the creation of Pangu. This book is directly applied to data analysis, so many less commonly used modules in data analysis will not be discussed.
The second edition of this book has been updated for Python 3.6, adding practical cases to show you how to solve a series of data analysis problems efficiently. You will learn the new versions of Panda, NumPy, IPython and Jupyter in reading.
4.r language
R is a language and operating environment for statistical analysis and drawing. However, R is more difficult. Please try carefully if you have no foundation! Recommended books:
Introduction and Practice of R Language
0 1 reasons for recommendation
This book explains how to play with data in R language in a simple way through three carefully selected examples. Incorporate the necessary professional skills of data scientists to teach readers how to store data into computer memory, how to convert data values in memory when necessary, and how to write their own programs with R and use them for data analysis and simulation operations.
Case promotion class
Active data: data analysis that drives business.
0 1 reasons for recommendation
Is a practical book to help enterprises solve business problems with data, with theories, methods and practical cases. It has four characteristics: business-driven, closed case, thinking-oriented, and actual combat restoration. At the same time, clear and coherent thinking and concise expression can not only help data analysis practitioners get started and improve, but also assist business departments and managers at all levels to make quantitative decisions.
Lean data analysis
0 1 reasons for recommendation
This book shows how to test your ideas, find real customers, create profitable products and improve corporate visibility. More than 30 case studies and insights from more than 65,438+000 well-known entrepreneurs around the world present you with hard-won, practice-tested entrepreneurial experience and valuable experience, which is worth reading by every entrepreneur and entrepreneur.