Scanner is a class available in ‘java.util’ package used to take input from numerous sources like a file, or console. The most common source of taking input is from standard input i.e. keyboard. The scanner class has few methods to take input of primitives and strings from the keyboard. We will understand scanner class and its various methods through this article. Scanner and nextChar() The following methods of Scanner class is used to take input − nextInt() − To take integer as an input. nextLong() − To take long as an input. nextDouble() − To take double as an ... Read More

String and Arrays are two distinct things. Array is a linear data structure that is used to store group of elements with similar datatypes but a string is a class in Java that stores a series of characters. Those characters are actually String-type objects. Since strings are objects we can say that string arrays are group of string-type objects. In this article, we will understand string arrays in java and perform some operations on them. String Arrays The string array is a combination of array and string both. Therefore, it has the properties of both array and string such ... Read More

A string is a class in Java that stores a series of characters. Those characters are actually String-type objects. The value of string is enclosed within double quotes. The string class is available in java.lang package. In this article, we will look into the storage mechanism of strings in java. String and Storage of String To create strings − Syntax String nameOfobject = “ values ”; Instance 1 String st1 = “Tutorix and Tutorialspoint”; Here, ‘st1’ is the reference variable and its values are in double quotes. We can also use new keyword to create ... Read More

The process of combining the elements of the given arrays is known as merging. This operation can be done in many ways using many techniques. Let us discuss all techniques that help in merging the given arrays in Python. Before getting into the techniques, let us understand how merging of arrays takes place with a simple Input output scenario. Input Output Scenario Consider two arrays arr1 and arr2. arr1 = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] arr2 = [ 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ] Now, the merged ... Read More

While considering the multi-dimensional arrays as an example, there is a method that is capable of finding the common elements present within a multi-dimensional array - intersection_update(). This method is used in order to find the common or intersecting elements present within the same array which is multi-dimensional in nature. Let us consider an input output scenario and then proceed with a program. Input Output Scenarios Consider a 2D array which is multi-dimensional in nature. arr = [[1, 2, 3, 4], [3, 4, 5, 6], [7, 8, 3, 4], [4, 9, 8, 3], [4, 3, 10, 12]] The ... Read More

What is Concatenation of Arrays? The process of combining the arrays into a single array or merging the arrays into a single array is known as Concatenation of arrays. This mechanism can be done in many ways using several techniques. Let us discuss all techniques that help in concatenation of arrays in Python. Input Output Scenarios Consider three arrays to perform concatenation. arr1 = [“ Hello ”, “ World ”, “ My ”, “ Name ”, “ is ”, “ Python ”] arr2 = [“ Hello ”, “ World ”, “ My ”, “ Name ”, “ is ”, “ ... Read More

There are several techniques that helps us to check whether the given arrays are equal or not. The comparison of an array will not depend on the indices of the elements, it will only compare whether that particular element in one array is present in the other array or not. Let us discuss few techniques that compares two arrays and checks whether they are equal or not. There are several techniques that helps us to check whether the given arrays are equal or not. The comparison of an array will not depend on the indices of the elements, it will ... Read More

Applying conditions on a data frame can be very beneficial for a programmer. We can validate data to make sure that it fits our model. We can manipulate the data frame by applying conditions and filter out irrelevant data from the data frame which improves data visualization. In this article, we will perform a similar operation of applying conditions to a PySpark data frame and dropping rows from it. Pyspark offers real time data processing. It is an API of Apache spark which allows the programmer to create spark frameworks in a local python environment. Example Now that we ... Read More

In this article, we will discuss the different methods to drop rows from a data frame base on a one or multiple conditions. These conditions will be applied on the columns and the rows will be dropped accordingly. We will use pandas to create a data frame as it offers multiple functions to manipulate the data frame. We will also create a dataset which will act as a reference for the data frame although it is not mandatory to create one, we can also use a CSV file or any other document. Pandas support multiple file types including: “CSV”, ... Read More

A dataset consists of a wide variety of values. These values can be a “string”, “integer”, “decimal” “Boolean” or even a “data structure”. These datasets are extremely valuable and can be used in various purposes. We can train model, interpret results, produce a hypothesis and build applications with the help a dataset. However, sometimes a dataset can contain values that are not necessary for our purpose. These values are called “NaN” (not a number). In this article, we will be dealing with these “NaN” or missing values. Our objective is to drop to those rows that contain any ... Read More