Several Big Data Visualization tools have been evaluated in this weeks paper. While the focus was primarily on R and Python with GUI tools, new tools are being introduced every day. Compare and contrast the use of R vs Python and identify the pros and cons of each. Provide an example of both programming languages with coding examples as well as your experience in using one or both programming languages in professional or personal work. If you have no experience with either language, please discuss how you foresee using either/both of these languages in visualizing data when analyzing big data.
Please make your initial post and two response posts substantive. A substantive post will do at least two of the following:
- Ask an interesting, thoughtful question pertaining to the topic
- Answer a question (in detail) posted by another student or the instructor
- Provide extensive additional information on the topic
- Explain, define, or analyze the topic in detail
- Share an applicable personal experience
- Provide an outside source that applies to the topic, along with additional information about the topic or the source (please cite properly in APA)
- Make an argument concerning the topic.
2 replays for below:
Even R programming language has a vast variety of libraries it mainly helps the data scientists to cleansing the data, evaluate the of machine learning, and creating visuals. The main difference between these two open-source programming languages is that R is more towards statistical analysis whereas Python is used in multiple ways and that includes machine learning as well.(R)
———————————————–
Programmers or software developers have been the primary users of Python, commonly then, at that point, this local area will turn to Python when they are preparing a project that require data examination. The people group of quantitative investigators, analysts, and researchers that contribute bundle applications to R is tremendous. The continuous support through mailing records and forums is enormous(R)
0 comments