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Articles on Trending Technologies
Technical articles with clear explanations and examples
Importance of the accumulate() method of JSONObject in Java?
A JSONObject is an unordered collection of a name and value pairs. A few important methods of JSONArray are accumulate(), put(), opt(), append(), write() and etc. The accumulate() method accumulates the values under a key and this method similar to the put() method except if there is an existing object stored under a key then a JSONArray can be stored under a key to hold all of the accumulated values. If there is an existing JSONArray then a new value can be added.Syntaxpublic JSONObject accumulate(java.lang.String key, java.lang.Object value) throws JSONExceptionExampleimport org.json.*; public class JSONAccumulateMethodTest { public static ...
Read MoreHow to convert a JSON object to an enum using Jackson in Java?
A JSONObject can parse the text from String to produce a Map kind of an object. An Enum can be used to define a collection of constants, when we need a predefined list of values which do not represent some kind of numeric or textual data then we can use an enum. We can convert a JSON object to an enum using the readValue() method of ObjectMapper class.In the below example, we can convert/deserialize a JSON object to Java enum using the Jackson library.Exampleimport com.fasterxml.jackson.databind.*; public class JSONToEnumTest { public static void main(String arg[]) throws Exception { ...
Read MoreHow to resize Image in Android App?
This example demonstrate about How to resize Image in Android App.Step 1 − Create a new project in Android Studio, go to File ⇒ New Project and fill all required details to create a new project.Step 2 − Add the following code to res/layout/activity_main.xml. Step 3 − Add the following code to src/MainActivity.javapackage app.tutorialspoint.com.sample ; import android.app.Activity ; import android.content.Intent ; import android.graphics.Bitmap ; import android.net.Uri ; import android.provider.MediaStore ; import android.support.v7.app.AppCompatActivity ; import android.os.Bundle ; import android.view.View ; import android.widget.ImageView ; import java.io.IOException ; ...
Read MoreWhich function should be used to load a package in R, require or library?
The main difference between require and library is that require was designed to use inside functions and library is used to load packages. If a package is not available then library throws an error on the other hand require gives a warning message.Using library> library(xyz) Error in library(xyz) : there is no package called ‘xyz’Using requirerequire(xyz) Loading required package: xyz Warning message: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called ‘xyz’Here we can see that the library shows an error and require gives a warning message, since warnings are mostly avoided ...
Read MoreHow to deal with "could not find function" error in R?
The error “could not find function” occurs due to the following reasons −Function name is incorrect. Always remember that function names are case sensitive in R.The package that contains the function was not installed. We have to install packages in R once before using any function contained by them. It can be done as install.packages("package_name")The package was not loaded before using the function. To use the function that is contained in a package we need to load the package and it can be done as library("package_name").Version of R is older where the function you are using does not exist.If you ...
Read MoreHow to do an inner join and outer join of two data frames in R?
An inner join return only the rows in which the left table have matching keys in the right table and an outer join returns all rows from both tables, join records from the left which have matching keys in the right table. This can be done by using merge function.ExampleInner Join> df1 = data.frame(CustomerId = c(1:5), Product = c(rep("Biscuit", 3), rep("Cream", 2))) > df1 CustomerId Product 1 1 Biscuit 2 2 Biscuit 3 3 Biscuit 4 4 Cream 5 5 Cream > df2 = data.frame(CustomerId = c(2, 5, 6), City = c(rep("Chicago", 2), rep("NewYorkCity", 1))) > df2 CustomerId City ...
Read MoreHow to make list of data frames in R?
This can be done by using list function.Example> df1
Read MoreHow to filter rows that contain a certain string in R?
We can do this by using filter and grepl function of dplyr package.ExampleConsider the mtcars data set.> data(mtcars) > head(mtcars) mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 Valiant 18.1 ...
Read MoreHow to change the orientation and font size of x-axis labels using ggplot2 in R?
This can be done by using theme argument in ggplot2Example> df df x y 1 long text label a -0.8080940 2 long text label b 0.2164785 3 long text label c 0.4694148 4 long text label d 0.7878956 5 long text label e -0.1836776 6 long text label f 0.7916155 7 long text label g 1.3170755 8 long text label h 0.4002917 9 long text label i 0.6890988 10 long text label j 0.6077572Plot is created as follows −> library(ggplot2) > ggplot(df, aes(x=x, y=y)) + geom_point() + theme(text = element_text(size=20), axis.text.x = element_text(angle=90, hjust=1))
Read MoreHow to select only numeric columns from an R data frame?
The easiest way to do it is by using select_if function of dplyr package but we can also do it through lapply.Using dplyr> df df X1 X2 X3 X4 X5 1 1 11 21 a k 2 2 12 22 b l 3 3 13 23 c m 4 4 14 24 d n 5 5 15 25 e o 6 6 16 26 f p 7 7 17 27 g q 8 8 18 28 h r 9 9 19 29 i s 10 10 20 30 j t >library("dplyr") > select_if(df, is.numeric) X1 X2 X3 1 1 11 21 2 2 12 22 3 3 13 23 4 4 14 24 5 5 15 25 6 6 16 26 7 7 17 27 8 8 18 28 9 9 19 29 10 10 20 30Using lapply> numeric_only df[ , numeric_only] X1 X2 X3 1 1 11 21 2 2 12 22 3 3 13 23 4 4 14 24 5 5 15 25 6 6 16 26 7 7 17 27 8 8 18 28 9 9 19 29 10 10 20 30
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