Ranking of a variable has many objectives such as defining order based on hierarchy but in data science, we use it mainly for analyzing non-parametric data. The ranking of a variable in an R data frame can be done by using rank function. For example, if we have a data frame df that contains column x then rank of values in x can be found as rank(df$x).Example Live DemoConsider the below data frame: x1

The default value of Y-axis tick marks using ggplot2 are taken by R using the provided data but we can set it by using scale_y_continuous function of ggplot2 package. For example, if we want to have values starting from 1 to 10 with a gap of 1 then we can use scale_y_continuous(breaks=seq(1,10,by=1)).Example Live DemoConsider the below data frame: x

If we want to match the names of a vector in sequence with string vector values in another vector having same values then pmatch function can be used. The pmatch function means pattern match hence it matches all the corresponding values and returns the index of the values. Check out the below examples to understand how it works.Example Live Demox1

Duplication is also a problem that we face during data analysis. We can find the rows with duplicated values in a particular column of an R data frame by using duplicated function inside the subset function. This will return only the duplicate rows based on the column we choose that means the first unique value will not be in the output.Example Live DemoConsider the below data frame: x1

The concatenation of string vectors will create combination of the values in the vectors thus, we can use them for interaction between/among the vectors. In R, we can use expand.grid along with apply to create such type of combinations as shown in the below examples.Example 1 Live Demox1

Instructors/educators often need to teach missing value imputation to their students; hence they require datasets that contains some missing values or they need to create one. We also have some data sets with missing values available in R such as airquality data in base R and food data in VIM package. There could be many other packages that contain data sets with missing values but it would take a lot of time to explore them. Thus, we have shared the example of airquality and some data sets from VIM package.Example 1 Live Demohead(airquality, 20)Output Ozone Solar.R Wind Temp Month Day 1 41 ... Read More

If a column in an R data frame has only two values 0 and 1 then we call it a binary column but it is not necessary that a binary column needs to be defined with 0 and 1 only but it is a general convention. To detect a binary column defined with 0 and 1 in an R data frame, we can use the apply function as shown in the below examples.ExampleConsider the below data frame − Live Demox1

With INNER JOIN only the matching elements are included in the result set. Non-matching elements are excluded from the result set.With LEFT OUTER JOIN all the matching elements + all the non-matching elements from the left collection are included in the result set.Let us understand implementing Left Outer Join with an example. Consider the following Department and Employee classes. Notice that, Employee Mary does not have a department assigned. An inner join will not include her record in the result set, where as a Left Outer Join will.Examplestatic class Program{    static void Main(string[] args){       var result = Employee.GetAllEmployees() ... Read More

Reflection is the process of describing the metadata of types, methods and fields in a code. The namespace System.Reflection enables you to obtain data about the loaded assemblies, the elements within them like classes, methods and value types. There are numerous classes of System.Reflection but the most commonly used ones are Assembly, AssemblyName, ConstructorInfo, MethodInfo, ParameterInfo, EventInfo, PropertyInfo, and MemberInfo.Examplestatic void Main(string[] args){    TypeInfo myType = typeof(TextInfo).GetTypeInfo();    IEnumerable properties = myType.DeclaredProperties;    IEnumerable methods = myType.DeclaredMethods;    Console.WriteLine(myType);    Console.WriteLine(properties);    Console.WriteLine(methods);    StringBuilder strBuilder = new StringBuilder();    Console.WriteLine();    strBuilder.Append("The properties are:");    foreach (PropertyInfo p ... Read More

The process of injecting (converting) coupled (dependent) objects into decoupled (independent) objects is called Dependency Injection.Types of Dependency InjectionThere are four types of DI −Constructor InjectionSetter InjectionInterface-based injectionService Locator InjectionInterface InjectionInterface Injection is similar to Getter and Setter DI, the Getter, and Setter DI use default getter and setter but Interface Injection uses support interface a kind of explicit getter and setter which sets the interface property.Examplepublic interface IService{    string ServiceMethod(); } public class ClaimService:IService{    public string ServiceMethod(){       return "ClaimService is running";    } } public class AdjudicationService:IService{    public string ServiceMethod(){       ... Read More