{"id":508,"date":"2016-10-21T12:35:04","date_gmt":"2016-10-21T12:35:04","guid":{"rendered":"http:\/\/kusuaks7\/?p=113"},"modified":"2025-03-14T09:21:46","modified_gmt":"2025-03-14T09:21:46","slug":"python-data-science","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/future-of-work\/python-data-science\/","title":{"rendered":"Is Python Becoming the King of the Data Science Forest?"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\tR has served as the de facto tool used for big data analytics. According to RedMonk’s bi-annual rankings<\/a> of the top 20 programming languages, as measured by activity on StackOverflow and GitHub repositories, \u00a0R is ranked #15 among all programming languages. This ranking is both surprising and impressive for a domain-specific language. \u00a0Interestingly, Python is at the top of the list among the top-dogs\u0097Java, Javascript and PHP\u0097that are used for general purpose web-programming. \u00a0Lesser-known languages such as Julia are also represented in the rankings, although not in the top-20 list. \u00a0The first quarter plot for 2014 ranking is shown here.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Despite R’s apparent success\u0097as\u00a0MongoDB’s\u00a0Matt Asays<\/a>\u00a0has argued\u0097while R was once the language of choice for data scientists, it is quickly ceding ground to Python.\u00a0One of the reasons for a perceived<\/em> decrease in R’s popularity it is argued is its\u00a0complex programming environment that requires special training.\u00a0According to\u00a0Robert Muenchen<\/a>\u00a0at the University of\u00a0Tennessee, even for data scientists who possess expertise in statistical tools such as\u00a0SAS, SPSS and Stata\u0097R remains a tough language to master. \u00a0This is largely because R uses misleading function and parameter names. If\u00a0SAS, SPSS and Stata use the sort command to sort data sets, R has the same command but it does not sort data sets; instead R uses the command to sort individual variables. \u00a0In R, one must use the order function to sort data sets and that too happens in a rather convoluted manner. \u00a0In addition, R suffers from sparse non-standard output, and it has too many commands to master. R also provides a sloppy control over variables and naming or remaining variables is an overly complex exercise, at least for the novice.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tPython, on the other hand, is much easier to master\u0097even though it may still be harder than other programming languages used to develop web applications. \u00a0The fact that Python is used to develop web applications is what makes it an attractive choice for data science. \u00a0If you are struggling to find qualified data scientists, why not train your existing Python developers to work in your data science teams? \u00a0Furthermore, given the wide applicability of the language, we are witnessing what\u00a0Tal Yarkoni<\/a>\u00a0of UT Austin calls the Pythonification\u00a0of tools that are appropriate for data science.\n
The increasing homogenization (Pythonification?) of the tools I use on a regular basis primarily reflects the spectacular recent growth of the Python ecosystem. A few years ago, you couldn\u0092t really do statistics in Python unless you wanted to spend most of your time pulling your hair out and wishing Python were more like R (which, is a pretty remarkable confession considering\u00a0what R is like<\/a>). Neuroimaging data could be analyzed in SPM (MATLAB-based), FSL, or a variety of other packages, but there was no viable full-featured, free, open-source Python alternative. Packages for machine learning, natural language processing, web application development, were only just starting to emerge.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThese days, tools for almost every aspect of scientific computing are readily available in Python. And in a growing number of cases, they’re eating the competition’s lunch.\n\nWhile there is little doubt that Python is going to become a dominant language for data scientists, how is it faring against other languages of the web? \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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The growing popularity of Python is not surprising given its versatility. \u00a0To be sure, R still is far more powerful when it comes to data analytics. \u00a0However, Python is catching up, but does this really mean that its large number of followers are going to supplant R? \u00a0The chart above needs to be nuanced because it compares apples and oranges. \u00a0Charts like these are often used to make misguided arguments about R’s impending demise. \u00a0So, how does demand for R compare with other statistical tools such as SAS?<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The growing popularity of Python is not surprising given its versatility. \u00a0To be sure, R still is far more powerful when it comes to data analytics. \u00a0However, Python is catching up, but does this really mean that its large number of followers are going to supplant R? \u00a0The chart above needs to be nuanced because it compares apples and oranges. \u00a0Charts like these are often used to make misguided arguments about R’s impending demise. \u00a0So, how does demand for R compare with other statistical tools such as SAS?<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\tThis helps us nuance our understanding and see that while Python has significant traction, given its use in domains other than data science, the demand for R is also on the rise and the latter is not going to become obsolete anytime soon. \u00a0R continues to enjoy popularity among academics.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tWe would love to hear how you are staffing your current teams and what role R and Python play in your environment.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tSee a follow-up post on this topic:\u00a0Can Python Replace R for Developing Predictive Models<\/a>?\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tNeed help with your R or Python project or simply\u00a0need data scientists and visualizers to augment your existing team? Post your project in the\u00a0Experfy Marketplace<\/a>\u00a0to solicit bids from\u00a0vetted\u00a0experts. Experfy has the world\u0092s top data experts, who specialize in specific industry data and can ask the right questions of your data. You can also email support@www.experfy.com for more information.<\/strong>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

R has served as the de facto tool used for big data analytics.  According to RedMonk’s bi-annual rankings of<\/p>\n","protected":false},"author":11,"featured_media":2867,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[182],"tags":[122,94,799,114],"ppma_author":[1606],"class_list":["post-508","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-future-of-work","tag-big-data","tag-data-science","tag-data-science-forest","tag-python"],"authors":[{"term_id":1606,"user_id":11,"is_guest":0,"slug":"cameron-turner","display_name":"Cameron Turner","avatar_url":{"url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2024\/09\/cameron.jpeg","url2x":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2024\/09\/cameron.jpeg"},"user_url":"","last_name":"Turner","first_name":"Cameron","job_title":"","description":""}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/508","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=508"}],"version-history":[{"count":5,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/508\/revisions"}],"predecessor-version":[{"id":37407,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/508\/revisions\/37407"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/2867"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=508"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=508"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=508"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=508"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}