assignment 3

Discussion 1

Visualization tools are accessible for displaying real-time data over time. They can capture all sorts of data from cameras, mobile devices, and a variety of sources. They can show all the data that can fit into the viewport. However, to study the complexity of the data, Visualization tools are most useful for displaying data as a sequence of metrics. Most visualization tools use the count tool to create a timeline and a frequency map. These can be compared with data that already have to compare the real-time data against. If the complexity of the data is simple, then the visualization tools are not very useful for studying the data. However, if the complexity is involved, then the visualization tools can be handy (Po et al., 2020).

R is an open-source and cross-platform scientific computing environment with graphical and statistical methods. The use of R for computational biology tasks enables visualization of large data sets and the review and modification of experimental protocols. The use of R for the development of computational methods to classify and classify genomes has demonstrated its usefulness in identifying features that are important in the classification of human pathogens. The use of R has become an integral part of genome-wide association studies (GWAS) and deep sequencing data analysis methods, which will benefit the research community. The R is a development in computational biology with multi-language capabilities. The numerical system was designed in the same paradigm as some electronic computers like the IBM PC and can perform subroutine calculations (Po, et al., 2020). The programming language, R, is known as a high-level programming language. In the field of biological sciences, the basic properties of this language include data collection, filtering, algebraic manipulation, and statistical analyses. In addition to the standard functions of the computing environment, R provides other useful functions such as running code under the control of other programs, communication, and interfacing with other machines. The R programming language is a descendant of the scientific languages C and Pascal (Zion & Tripathy, 2020).

Python is a compelling programming language that is developed and used by computer scientists around the world. It is being used to develop software for architecture, design, optimization, research, testing and development. It is also being used in several industries as a computer programming language. The use of Python programming language to develop sophisticated applications is always a big choice, and many companies have adopted Python language to develop their software. It has become the preferred language for the development of modern web applications and is also being used as a scripting language for numerous web sites. Although there are many software programmers all around the world using other programming languages like C++, Java, PHP and Python, every single one of them knows about the pros and cons of each programming language. Therefore, learning a new programming language is always an exhilarating experience. Therefore, many graduates have been using various programming languages, but a lot of them are still looking for some gain in their career. For example, R offers several excellent packages, such as ggplot2 and tibble2. Python, on the other hand, offers several great packages such as NumPy, pandas and in-memory computing. Both languages are suitable for almost any kind of data analysis. Python and R both have a similar syntax, working with a .txt or .csv file. Python has a rich set of data types and the tremendous support for matrices in Python, whereas R is perfect for data analysis (Zion & Tripathy, 2020).

Discussion 2

One of the effective tools used by the data analysts, researchers of the data require extensive use of a simulation process and the visualization process is that is designed to cater better representation of the information in a graphical way that allows representation of huge information in a systematic approach in minimum space that the specific attributes for, functioning, and display, effective use of images and videos to be created. Visualization has become up and of the primary part of the analysis, the process to effectively gain a better understanding of the existing information, develop appropriate methods of simulation process to define the probable future information generation to be generated, evaluated using visualization tools that can provide easy understanding of the information in a systematic approach.

R is a programming language used by researchers, developers, analysts that allows the representation of visualization effects in systematic ways with the rich libraries that are available created by many users and contributing two words development of the programming language over a period. With the specific requirements identified by the researchers and developing of solutions has allowed the programming language to have all the possible solutions that are required for any visualization effects to be conducted, provision of reflects functionalities has allowed effective use of visualization techniques, implement graphs, other absent a shun types effectively using the programming language (Kirk, 2016).

Python is a new programming language in recent times, has developed several visualization tools to be incorporated into packages that render all the basic capabilities, still to have several functionalities that are required for effective visualization, the representation layers are still developing, to the language concentrating on more on string processing is yet to develop statistical and visualization tools that can be effectively used for developing better visualization programs if and representations to be created (Ohri, 2017).

Please make sure two response posts to given discussions substantive. A substantive post will do at least TWO of the following:

1.Ask an interesting, thoughtful question pertaining to the topic

2.Answer a question (in detail) posted by another student or the instructor

3.Provide extensive additional information on the topic

4.Explain, define, or analyze the topic in detail

5.Share an applicable personal experience

6.Provide an outside source (for example, an article from the UC Library) that applies to the topic,

along with additional information about the topic or the source (please cite properly in APA)

7.Make an argument concerning the topic.

8.At least one scholarly source should be used in the initial discussion thread. Be sure to use information from your readings and other sources from the UC Library. Use proper citations and references in your post.