Best Programming Language For Data Visualization

1. Brazil's news website, Visualoop, a visualization site that brings together information graphs and data from the Internet, continues this year to identify the best large data visualization tool of the year. "We're struggling to pick out these 20 new platforms or tools-if you're a loyal reader of our weekly data coverage, you might remember a few of our lists." "In this list they ignore new versions and updates to existing tools, such as: Cartodb, Mapbox, Tableau, D3.js,...

Which of the following 5 languages are NODE, LUA, Python, Ruby, R, and which will be better applied in the 2014? I don't hesitate to choose R. 　　R is not only 2014, but also the protagonist for a longer period of time. 1. My programming background programmer, Architect, from the beginning of programming to today, has been convinced that Java is the language to change the world, Java has done, and has been very brilliant. But when the world of Java is becoming bigger and larger, when it becomes omnipotent, it is not professional enough for other languages to develop ...

The following small series summarizes 10 best data mining tools for everyone, which can help you analyze big data from various angles and make correct business decisions through data.

With the development and popularity of artificial intelligence technology, Python has surpassed many other programming languages and has become one of the most popular and most commonly used programming languages in the field of machine learning.

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

2014 China Large data technology conference officially fell on December 14, nearly hundred technical experts here to share their latest research and practical results, this article from China Economic Network management consultant Yang, the main interpretation of the relationship between large data and in-depth learning, as well as the future development of industry technology. The following is the author of the original: December 2014 12-14th, sponsored by the China Computer Society (CCF), CCF large data expert committee contractor, the Chinese Academy of Sciences and CSDN jointly co-organized to promote large data research, application and industrial development as the main theme of the 2014 China Big ...

Analysis is the core of all enterprise data deployments. Relational databases are still the best technology for running transactional applications (which is certainly critical for most businesses), but when it comes to data analysis, relational databases can be stressful. The adoption of an enterprise's Apache Hadoop (or a large data system like Hadoop) reflects their focus on performing analysis, rather than simply focusing on storage transactions. To successfully implement a Hadoop or class Hadoop system with analysis capabilities, the enterprise must address some of the following 4 categories to ask ...

Why create a Julia programming language? In a word, because we thirst for knowledge, constant pursuit. We have the core users of MATLAB, there are good at Lisp hackers, Pythonistas and rubyists experts also have a lot; In addition, there are some Perl Daniel, some developers used Mathematica before we had a little understanding of the fur. In other words, they understand more than just the fur, more than others, the development of R language. and C language for us is a deserted island. I ...

Introduction: This article explores the development of the Julia Language and its new features. The author thinks that the birth of a new language is bound to set off a new whirlwind, developers in the enjoyment of it to bring fun while also arguing for its existence value, whether Julia can bring new gospel to developers? Let's go into it together: Why create the Julia programming language? In a word, because we thirst for knowledge, constant pursuit. We have the core users of MATLAB, there are good at Lisp hackers, Pythonistas and Ru ...