Articles on Trending Technologies

Technical articles with clear explanations and examples

How to show values in boxplot in R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 5K+ Views

The main values in a boxplot are minimum, first quartile, median, third quartile, and the maximum, and this group of values is also called five-number summary. Therefore, if we want to show values in boxplot then we can use text function and provide the five-number summary and labels with fivenum function as shown in the below examples.Example1x

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How to create a horizontal boxplot in base R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 3K+ Views

To create a horizontal boxplot in base R, we can set the horizontal argument inside boxplot function to TRUE. For example, if we have a vector called x then the horizontal histogram of that vector can be created by using the command boxplot(x,horizontal=TRUE).Example1x

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How to create normal random variables with specific correlation between them in R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 719 Views

To create normal random variables with specific correlation between them, we can use mvrnorm function of MASS package. For example, if we want to create two variables of size 10 with means equal to 2 and 4 and standard deviation of 0.5 then it can be done by using the command −mvrnorm(10,mu=c(2,4),Sigma=matrix(c(1,0.5,0.5,1),ncol=2),empirical=TRUE)Example1library(MASS) X

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How to find prime factors of a number in R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 1K+ Views

A prime number is the number that is only divisible by itself and one. These prime numbers can also divide other numbers hence they become a factor of those numbers. For example, 5 is a prime number and it also divides 20. To find the prime factors of a number, we can use primeFactors function of numbers package.Exampleslibrary(numbers)primeFactors(100)[1] 2 2 5 5primeFactors(1000)[1] 2 2 2 5 5 5 primeFactors(32547)[1] 3 19 571primeFactors(12354767)[1] 17 726751 primeFactors(21457)[1] 43 499primeFactors(99)[1] 3 3 11 primeFactors(365748)[1] 2 2 3 29 1051primeFactors(214687)[1] 11 29 673 primeFactors(3587497)[1] 3587497primeFactors(35874)[1] 2 3 3 1993 primeFactors(268713)[1] 3 3 73 409primeFactors(298473)[1] ...

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How to subset a data.table object using a range of values in R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 3K+ Views

To subset a data.table object using a range of values, we can use single square brackets and choose the range using %between%. For example, if we have a data.table object DT that contains a column x and the values in x ranges from 1 to 10 then we can subset DT for values between 3 to 8 by using the command DT[DT$x %between% c(3,8)].Example1Loading data.table package and creating a data.table object −library(data.table) x1

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How to create empty bar plot in base R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 452 Views

To create a bar plot in base R, we can use the function barplot and pass the vector or column of the data frame for which we want to create the bar plot but the bars created by using barplot by default has grey color. Therefore, if we want to create an empty bar plot then setting the color of bars to NA will make the plot an empty bar plot.Example1x

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Object-oriented Life Cycle Model in Software Engineering

Vineet Nanda
Vineet Nanda
Updated on 06-Mar-2021 19K+ Views

The object-oriented life cycle model considers 'objects' as the basis of the software engineering process. The development team starts by observing and analyzing the system they intend to develop before defining the requirements. Once the process is over, they focus on identifying the objects of the system. Now, an object could be anything; it can have a physical existence like a customer, car, etc. An object also constitutes intangible elements like a process or a project.Advantages of Object-Oriented Life Cycle ModelApart from enhancing the system performance, object-oriented programming offers some advantages such as:Since it is data-focused and easy to work ...

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Life Cycle Phases of Data Analytics

Vineet Nanda
Vineet Nanda
Updated on 06-Mar-2021 6K+ Views

Life Cycle Phases of Data AnalyticsThe Data Analytics Lifecycle is a cyclic process which explains, in six stages, how information in made, collected, processed, implemented, and analyzed for different objectives.Data DiscoveryThis is the initial phase to set your project's objectives and find ways to achieve a complete data analytics lifecycle. Start with defining your business domain and ensure you have enough resources (time, technology, data, and people) to achieve your goals.The biggest challenge in this phase is to accumulate enough information. You need to draft an analytic plan, which requires some serious leg work.Accumulate resourcesFirst, you have to analyze the ...

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Software Inspection Guiding Principles

Vineet Nanda
Vineet Nanda
Updated on 06-Mar-2021 451 Views

Testing Shows the Presence of DefectsEach application must pass through a search of testing phases such as system integration testing, user acceptance testing and beta testing, etc. before they are released into production. Some form of defects will always be found, Regardless of how much testing one conducts.The core purpose of the testing team should focus on finding the defects in an application. The inspection team must use different methods to discover as many errors as they can. It helps in reducing the number of undiscovered errors in a software application. Even though the testing team fails to find any ...

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How to create a histogram without bins in base R?

Nizamuddin Siddiqui
Nizamuddin Siddiqui
Updated on 06-Mar-2021 424 Views

We can set type argument to s in plot function to create a histogram without bins but first we need to create the histogram and store it in an object. For example, if we have a vector say x then the histogram of x can be stored in an object called p then we can use the command plot(c(p$counts,0),type="s") to create the histogram without bins as shown in the below example.Example> x p plot(c(p$counts,0),type="s")Output

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