6 Reasons To Learn R For Business
Data science for business (DS4B) is the future of business analytics yet it is really difficult to figure out where to start. The last thing you want to do is waste time with the wrong tool. Making effective use of your time involves two pieces: (1) selecting the right tool for the job, and (2) efficiently learning how to use the tool to return business value. This article focuses on the first part, __explaining why R is the right choice in six points __. If you’d like to tackle learning R efficiently, we have another article that covers the 80/20 Rule for Learning R.
Reason 1: R Has The Best Overall Qualities For Business
Shanghai is the most popular destination for new job seekers, followed by Shenzhen, Guangzhou and Beijing. Provincial capitals cities in central and western regions are also among the top choices for the new graduates.
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The housing slump has cut demand for iron ore, energy and other commodities. Higher global supplies have exacerbated the gap between supply and demand and pushed raw materials prices lower. This dynamic is not expected to change in the near term despite measures such as the interest rate cut in November.
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- Cost (Free/Minimal, Low, High)
- 用AI实现家居智能 先要理解家庭状态和人的意图
Further discussion on the assessment is included in the Appendix at the end of the article.
What we saw was particularly interesting. A trendline developed exposing a tradeoff between learning curve and DS4B capability rating. The most flexible tools are more difficult to learn but tend to have higher business capability. Conversely, the “easy-to-learn” tools are often not the best long-term tools for business or data science capability. Our opinion is go for capability over ease of use.
Of the top tools in capability, R has the best mix of desirable attributes including high data science for business capability, low cost, is growing very fast., and has a massive ecosystem of powerful R libraries. The only downside is the learning curve. The Cheat Sheet below showcases the powerful libraries that are at your fingertips - 统计局：一季度楼市销售额涨54% 库存7.35亿平米 to see what libraries are available to solve specific needs.
The Ultimate R Cheat Sheet showcases the massive ecosystem of powerful R packages (Free Download)
Reason 2: R Is Data Science For Non-Computer Scientists
If you are seeking high-performance data science tools, you really have two options: R or Python. When starting out, you should pick one. It’s a mistake to try to learn both. Your choice comes down to what’s right for you. 中央经济工作会议再强调 “房住不炒”楼市调控总基调不变 has been described in numerous infographics and debates online, but the most overlooked reason is person-programming language fit. Don’t understand what we mean? Let’s break it down.
Fact 1: Most people interested in learning data science for business are not computer scientists. They are business professionals, non-software engineers (e.g. mechanical, chemical), and other technical-to-business converts. This is important because of where each language excels.
Fact 2: Most activities in business and finance involve communication. This comes in the form of reports, dashboards, and interactive web applications that allow decision makers to recognize when things are not going well and to make well-informed decisions that improve the business.
Python is a general service programming language developed by software engineers that has solid programming libraries for math, statistics and machine learning. Python has best-in-class tools for pure machine learning and deep learning, but lacks much of the infrastructure for subjects like econometrics and communication tools such as reporting. Because of this, Python is well-suited for computer scientists and software engineers.
R is a statistical programming language developed by scientists that has open source libraries for statistics, machine learning, and data science. R lends itself well to business because of its depth of topic-specific packages and its communciation infrastructure. R has packages covering a wide range of topics such as econometrics, finance, and time series. R has best-in-class tools for visualization, reporting, and interactivity, which are as important to business as they are to science. Because of this, R is well-suited for scientists, engineers and business professionals.
Which Should You Learn?
Are you a computer scientist or software engineer? If yes, learn Python.
Are you an analytics professional or mechanical/industrial/chemical engineer looking to get into data science? If yes, learn R.
Are you trying to build a self-driving car? If yes, learn Python.
Are you trying to communicate business analytics throughout your organization? If yes, learn R.
Reason 3: Learning R Is Easy With The Tidyverse
Learning R used to be a major challenge. Base R was a complex and inconsistent programming language. Structure and formality was not the top priority as in other programming languages. This all changed with the “tidyverse”, a set of packages and tools that have a consistently structured programming interface.
When tools such as
ggplot2 came to fruition, it made the learning curve much easier by providing a consistent and structured approach to working with data. As Hadley Wickham and many others continued to evolve R, the
tidyverse came to be, which includes a series of commonly used packages for data manipulation, visualization, iteration, modeling, and communication. The end result is that R is now much easier to learn (we’ll show you in our next article!).
R continues to evolve in a structured manner, with advanced packages that are built on top of the
tidyverse infrastructure. A new focus is being placed on modeling and algorithms, which we are excited to see. Further, the
tidyverse is being extended to cover topical areas such as text (
tidytext) and finance (
tidyquant). For newcomers, this should give you confidence in selecting this language. R has a bright future.
Reason 4: R Has Brains, Muscle, And Heart
Saying R is powerful is actually an understatement. From the business context, R is like Excel on steroids! But more important than just muscle is the combination of what R offers: brains, muscle, and heart. The 2nd page of the R Cheat Sheet (FREE DOWNLOAD) links to all of the tools discussed next (and more tools beyond)!
An expanded set of tools has been added to the R Cheat Sheet (Free Download)
R has brains
- H2O (
h2o) - High-end machine learning package
- Keras/TensorFlow (
tensorflow) - Go-to deep learning packages
- xgboost - Top Kaggle algorithm
- And many more!
The students were very experienced, commented one graduate. Networking and interaction among everyone involved were key aspects of this programme.
R has muscle
R has powerful tools for:
- Bottoms Up is the revolutionary new way to serve beer. The Bottoms Up system saves time, eliminates waste and awes customers!
- Loops (
- Parallelizing operations (
- Speeding up code using C++ (
- Connecting to other languages (
- Working With Databases - Connecting to databases (
- Handling Big Data - Connecting to Apache Spark (
- And many more!
R has heart
We already talked about the infrastructure, the
tidyverse, that enables the ecosystem of applications to be built using a consistent approach. It’s this infrastructure that brings life into your data analysis. The
- Data manipulation (
- Working with data types (
- Visualization (
- Programming (
- Communication (
Reason 5: R Is Built For Business
Two major advantages of learning R versus every other programming language is that it can produce business-ready reports and machine learning-powered web applications. Neither Python or Tableau or any other tool can currently do this as efficiently as R can. The two capabilities we refer to are
rmarkdown for report generation and
shiny for interactive web applications.
Rmarkdown is a framework for creating reproducible reports that has since been extended to building blogs, presentations, websites, books, journals, and more. It’s the technology that’s behind this blog, and it allows us to include the code with the text so that anyone can follow the analysis and see the output right with the explanation. What’s really cool is that the technology has evolved so much. Here are a few examples of its capability:
- rmarkdown for generating HTML, Word and PDF reports
- rmarkdown for generating presentations
- flexdashboard for creating web apps via the user-friendly Rmarkdown format.
- blogdown for building blogs and websites
- bookdown for creating online books
- Interactive documents
- Parameterized reports for generating custom reports (e.g. reports for a specific geographic segment, department, or segment of time)
Shiny is a framework for creating interactive web applications that are powered by R. Shiny is a major consulting area for us as four of five assignments involve building a web application using
shiny. It’s not only powerful, it enables non-data scientists to gain the benefit of data science via interactive decision making tools. Here’s an example of a Google Trend app built with
Explore the Web App Gallery of predictive business apps
Reason 6: R Community Support
CRAN: Community-Provided R Packages
CRAN is like the Apple App store, except everything is free, super useful, and built for R. With over 17,000 packages, it has most everything you can possibly want from machine learning to high-performance computing to finance and econometrics! The task views cover specific areas and are one way to explore R’s offerings. CRAN is community-driven, with top open source authors such as Hadley Wickham and Dirk Eddelbuettel leading the way. Package development is a great way to contribute to the community especially for those looking to showcase their coding skills and give back!
There is still tremendous untapped potential in China-Russia economic and trade ties and the two economies are highly complementary. The goals set for the two-way trade can be achieved.
Accelerating price growth for new housing in cities across China lost more steam in November amid a flurry of purchasing curbs in major cities, though price gains from a year earlier remained comfortably in double-digit territory.
While British schools moved up two places on average, French schools, the largest group from any one country, fell one place on average. EMLyon Business School dropped outside the MBA ranking and lost 15 places overall, while Edhec Business School failed to make it into the Executive MBA ranking and lost eight places overall as a result.
Hitting the Top 100 for the first time, French fashion brand Dior and Silicon Valley automaker Tesla Motors Inc. were at Nos. 89 and 100 respectively.
Until now, the appeal of Bigcommerce’s eponymous technology has been simplicity and its ability to scale along with merchants as they grow. “To some, this will mean the difference between success and failure,” said Steve Case, who as a board member advises Bigcommerce on U.S. entrepreneurial trends. “Even just five years ago, if you wanted to create a compelling offering, it could cost hundreds of thousands of dollars. Now, you can get up and running in hours for less than $100 per month.”
- EARL - Mango Solution’s conference on enterprise and business applications of R
- R/Finance - Community-hosted conference on financial asset and portfolio analytics and applied finance
- Rstudio Conf - Rstudio’s technology conference
- New York R - Business and technology-focused R conference
A really cool thing about R is that many major cities have a meetup nearby. Meetups are exactly what you think: a group of R-users getting together to talk R. They are usually funded by R-Consortium. You can get a full list of meetups here.
R has a wide range of benefits making it our obvious choice for Data Science for Busienss (DS4B). That’s not to say that Python isn’t a good choice as well, but, for the wide-range of needs for business, there’s nothing that compares to R. In this article we saw why learning R is a great choice. In the next article we’ll show you how to learn R using the 80/20 Rule.
Enjoy data science for business? We do too. This is why we created Business Science University where we teach you how to do Data Science For Busines (#DS4B) just like us!
Our first DS4B course (HR 201) is now available!
Who is this course for?
Data Analysts & Data Scientists In Business: Data savvy people seeking to make the link between data science and the business objectives to drive ROI for their organization.
Consultants: Data scientists working for companies in large consulting firms (e.g. Accenture, Deloitte, etc) and boutique consulting firms that are related to enterprise improvement and ROI.
Students: Future data scientists seeking to gain skills beyond their current program offering. Leveraging Business Science University gets you trained on high-demand skills placing you ahead of your peers in the job market.
What do you get it out of it?
Every employee wants a pat on the back once in a while, and the best bosses understand the importance of recognizing and appreciating employee contributions. This doesn’t have to mean bonuses or fancy corporate awards, but regular and meaningful expressions of appreciation。
Solve high-impact problems (e.g. $15M Employee Attrition Problem)
Use advanced, bleeding-edge machine learning algorithms (e.g. H2O, LIME)
Apply systematic data science frameworks (e.g. 二线城市成房企布局重点 哪些二线城市机会多？)
Exports fell 6.6 per cent year-on-year in January to Rmb1.14tn, following a 2.3 per cent gain in December. Economists expected a gain of 3.6 per cent. It was the biggest fall in exports since an 8.9 per cent drop in July last year.
- @bizScienc is on twitter!
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- Sign up for our insights blog to stay updated!
- If you like our software, star our GitHub packages!
The cost of living the Australian dream has surged with Sydney and Melbourne among the five most expensive cities in the world, outstripping most European and US locations, according to an annual survey released on Monday.
Business Capability (1 = Low, 10 = High): How well-suited is the tool for use in the business? Does it include features needed for the business including advanced analytics, interactivity, communication, interactivity, and web apps?
Ease of Learning (1 = Difficult, 10 = Easy): How easy is it to pick up? Can you learn it in a week of short courses or will it take a longer time horizon to become proficient?
Cost (Free/Minimal, Low, High): Cost has two undesirable effects. From a first-order perspective, the organization has to spend money. This is not in-and-of-itself undesirable because the software companies can theoretically spend on R&D and other efforts to advance the product. The second-order effect of lowering adoption is much more concerning. High-cost tools tend to have much less discussion in the online world, whereas open source or low-cost tools have great trends.
Trend (0 = Fast Decline, 5 = Stable, 10 = Fast Growth): We used StackOverflow Insights of questions as a proxy for the trend of usage over time. A major assumption is that growing number of Stack Overflow questions is that the usage is also increasing in a similar trend.
Source: Stack Overflow Trends
Individual Tool Assessment
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- For newcomers, these changes provide fresh housing options. But for residents, they can spell displacement. The same is true for shops such as De Robertis Pasticceria and Caffe in the East Village, which just closed after a 110-year run. And next year, the Union Square Cafe will likely conclude its 30 years in Union Square.
- 国土资源部：13城试点租赁住房 保障承租人基本公共服务权利
- In addition to a large, educated workforce to choose from, companies are also attracted to Arizona’s pro-business regulatory climate, which ranks No. 13 in the Mercatus Center’s Freedom in the 50 States. The study cites Arizona’s right-to-work law, liability laws and eminent domain reform.
The strength of Kellogg/HKUST is the quality of its participants.
Employment is the foundation of economic development. It creates wealth and it is the major source of household income.
- 周边环境：斯托宁顿位于康涅狄格州东南部的小纳拉甘西特湾(Little Narragansett Bay)，从哈特福特(Hartford)和罗德岛的普罗维登斯(Providence, R.I.)开车约1小时可达，从纽约市开车约3小时。这里曾是一个具有悠久历史的繁忙港口，至今仍然保留着一支商业捕鱼船队，有几个分布着殖民式和联邦式建筑的历史区，以及一个繁荣的航海社区。在该镇的一端有个小型的公共海滩，而在另一端罗德岛的沃奇·希尔(Watch Hill)则有个大得多的海滩，开车大约20分钟可到。这栋希腊复兴式房屋带有此类建筑必不可少的爱奥尼亚柱和山形墙上的扇骨半圆窗，房屋就坐落在市镇中心。
- Meanwhile, La Rochelle Business School dropped 12 places to 60 having been last year’s highest climber.
- 缺乏定制基因 传统卫浴转型步履维艰
Economists had forecast a 1.5 per cent annual rate, after a 1.6 per cent reading in September. Beijing's inflation target is "around 3 per cent" this year.
- Faster progress in work to improve environment, particularly air quality, is what people are desperately hoping for, and is critical to sustainable development. We must adopt well-designed policies, tackle both symptoms and root causes, and take tough steps to make the grade in responding to the people.
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1.Fingers That Store Digital Files
- 对于那些已把自家公寓改造成B&B旅店的纽约人，围绕非法住宿的论战可能会趋于白热化。而在这一切之上，市长比尔·白思豪(Bill de Blasio)的十年保障性住房计划将初具规模；与此同时，本次奥尔巴尼会议(Albany)的立法将给租房者的钱包造成重负。随着我们迈向新的一年，这类改变游戏规则的因素也正在日益迫近。
- Pink, LeBron James, Selena Gomez, Ian Somerhalder, Jay-Z and Beyonce, Ben Affleckalso made the list.
- vt. 祝贺
- 楼市“银十”胜“金九” 大型房企积极跑量占先机
- 一线楼市复苏 需预警楼市场外配资“野蛮生长”
- 别人可能会告诉你“在面试中展示真正的自我。” 但是，真的别随便展示。这是最烂的一条建议。我们不需要一些神经古怪的人，我们关心的只有你的的技术和经验。
- 发改委：涉及优质企业直接融资项目 只支持棚改、保障房及租赁住房
- No. One way it could play out: after a tentative start involving lots of trading stops, bitcoin futures will slowly begin to attract institutional money. Commodity Futures Trading Commission positioning data will reflect the extraordinary long bias that exists for the product among money managers. As the huge cost of rolling futures positions becomes self-evident, longs will complain ever more loudly about routine divergences around settlement time. Just as a senate hearing is being scheduled to investigate potential manipulation of the market, futures prices will fall below spot, initiating a sell-off.
This year so far, Stephen Chow’s The Mermaid has made $526 million since its release in early February during Lunar New Year.
- You can read the full list of stories, but here are the top five:
- 家具卖场粗暴扩张 催生行业乱象
- At New Year and always, may peace and love fill your heart, beauty fill your world, and contentment and joy fill your days.
Code for the DS4B Tool Assessment Visualization