Sr. No.KeySpring AOPAspectJ AOP1BasicIt is a simple implementation of AOP technology. It can be applied only the beans.It is a complete implementation of the AOP technology in Java. It can be applied in any java class.2Design Pattern  It uses the proxy pattern so aspects are applied on proxies objectIt doesn't use proxy pattern aspects are directly applied on the code.3PontCutsIt supports only method level points cutsNo Restriction4Weaving of AspectsThe weaving of Aspects will be performed by the container at container start-up Weaving of aspect can perform with a post compilation of your code through bytecode modification5Nested MethodAspects can’t be applied when ... Read More

Spring framework supports five types of bean scope −SingletonPrototypeRequestSessionGlobal SessionAs per the spring documentation −Singleton − It returns a single bean instance per Spring IoC container. This single instance is stored in a cache of such singleton beans, and all subsequent requests and references for that named bean return the cached object.Spring singleton is different than Java singleton. In java, one instance of the bean is created per JVM whereas in spring, one instance of the bean is created per application context.Proptype −As per the spring documentation −Spring does not manage the complete lifecycle of a prototype bean: the container ... Read More

 Spring supports multiple types annotations such as @Component, @Controller, @service @Repository and @Bean. All theses can be found under the org.springframework.stereotype package.When classes in our application are annotated with any of the above mentioned annotation then during project startup spring scan(using @componentScan) each class and inject the instance of the classes to the IOC container. Another thing the @ComponentScan would do is running the methods with @Bean on it and restore the return object to the Ioc Container as a bean.Sr. No.Key@Bean@Component1Auto detectionIt is used to explicitly declare a single bean, rather than letting Spring do it automatically. If any class ... Read More

Factory and Dependency injection both are the design pattern which can be used to enhance loose coupling abilities between the software components. Factory design pattern is used to create objects. But, injection and life cycle management of the object should be handled by programmer within the application. There is no way to configure everything in a single place. Therefore, programmers need to call object creation logic wherever it needed which eventually hinder the loose coupling abilities.In DI design pattern, creation of object, injecting of the instance and life cycle management of the instance can be handled outside the code. In spring, ... Read More

Inversion of control is a design principle which helps to invert the control of object creation.According to the paper written by Martin Fowler , inversion of control is the principle where the control flow of a program is inverted: instead of the programmer controlling the flow of a program, the external sources (framework, services, other components) take control of it. It's like we plug something into something else. He mentioned an example about EJB 2.0.Dependency Injection is a design pattern which implements IOC principle. DI provides objects that an object needs. Let’s say, class X is dependent on Y. So ... Read More

Dependency Injection is a practice to pass dependent object to other objects. Spring has two types of Dependency Injection :Constructor based Injection -When container call the constructor of the class. It should be used for mandatory dependencies.Let’s say Class X is tightly  dependent on Class Y then we should use constructor based injection.  Setter based Injection - It can be used by calling setter methods on your beans. It should be used for optional dependencies.Both types of injection has their own pros and cons. Below is a list of some differences −Sr. No.KeyConstructor based InjectionSetter based Injection1CircularIt doesn’t allow to ... Read More

When the number of categories is large in numbers for a variable and we want to create a bar plot then the display of the bar plot becomes a little ambiguous because the bars are plotted very close to each other. To make the bars clearly visible, we can reduce the width of the bars and set different colors for them to make them visually attractive.geom_bar(width=0.2,color="red")Consider the below data frame −x

When we find the summary statistics of a data frame then the output is returned as a table and each of the column records the minimum, first quartile, median, median, third quartile, and maximum with their names. If we want to save this summary as a data frame then it is better to calculate it with apply function and store it as data.frame.ExampleConsider the below data frame − Live Demox1

In data analysis, often we require to determine the minimum and maximum values because these values help us to understand the limits of a column or variable under consideration. This can be done by using which.max for maximum and which.min for minimum with single square brackets to extract the rows.ExampleConsider the below data frame − Live Demox1

When we join or combine plots using grid.arrange the scales of the first plot comes in between as X-axis even if the independent variable in both of the plots is same.Therefore, we might want to remove the space between the plots while joining to get only one X-axis. This can be done by using theme function.ExampleConsider the below data frame − Live Demoset.seed(123) x