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The Java filter() method allows us to strain elements of the stream based on the specified condition. It is a part of higher-order function that is used to apply a certain behavior on stream items. This method takes a predicate as an argument and returns a list of elements that match the predicate. But the question arises here is that how this filter() method works in the background. This article aims to explain this question through some example programs. Working of filter() method in Background Before going deep into the filter() method, let’s familiarize ourselves with I/O Streams. Itis an ... Read More
The manipulation of date and time values is a crucial aspect of programming, and the Python language provides a useful built−in module called datetime for this purpose. However, in certain situations, it may be necessary to convert a DateTime object into an integer value in order to perform specific operations or calculations. There are various approaches to converting DateTime to an integer in Python, each with its own set of advantages and disadvantages. In this article, we will delve into these methods and examine when each one is appropriate to use. By the end of this article, you will have ... Read More
Python has become one of the most popular programming languages in the world, renowned for its simplicity, versatility, and vast ecosystem of libraries and frameworks. Alongside Python, there is PySpark, a powerful tool for big data processing that harnesses the distributed computing capabilities of Apache Spark. By combining the ease of Python with the scalability of Spark, developers can tackle large−scale data analysis and processing tasks efficiently. In this tutorial, we will explore the process of converting a list of dictionaries into a PySpark DataFrame, a fundamental data structure that enables efficient data manipulation and analysis in PySpark. In the ... Read More
Django is a fantastic web framework that has gained popularity among developers for its capability to create powerful web applications swiftly and with ease. One of its notable strengths is the flexibility to integrate with various third−party libraries and tools. In this article, we'll explore how to transform model data into JSON format utilizing Django. JSON, also known as JavaScript Object Notation, is a user−friendly data format that simplifies the exchange of data between servers and clients. It's a favorite among developers because of its uncomplicated structure and versatility. JSON can be read and written with ease, and several programming ... Read More
Numpy is a powerful Python library that serves to store and manipulate large, multi-dimensional arrays. Although it is fast and more efficient than other similar collections like lists, we can further enhance its performance by using the parallelizing mechanism. Parallelizing means splitting the tasks into multiple processes to achieve one single goal. Python provides several ways to parallelize a numpy vector operation including multiprocessing and numexpr module. Python Programs for Parallelizing a NumPy Vector Operation Let's discuss the ways to parallelize a numpy vector: Using multiprocessing Every Python program is considered as one single process and ... Read More
Pandas is a powerful Python library mainly used for data analysis. Since it contains large and complicated numeric datasets that are difficult to understand, we need to plot these datasets which makes it easy to visualize relationships within the given dataset. Python provides several libraries such as Matplotlib, Plotly and Seaborn to create informative plots from the given data with ease. In this article, we will show how to plot the size of each group in a Groupby object in Pandas. Python Program to Plot the Size of each Group in a Groupby Object To plot the ... Read More
GeoPandas, a widely used Python library build on top of the Pandas library to include the support of geospatial data. Here, geospatial data or geodata describes the information related to the various locations on Earth's surface. These datasets have many use cases including visualization of maps, urban planning, analysis of trade locations, network planning and so forth. In this article, we are going to explore how the GeoPandas library works and also, how to plot geospatial data using GeoPandas. Plotting Geospatial data using GeoPandas in Python Since GeoPandas extends the features of the Pandas library, we need to ... Read More
Python is a versatile and widespread programming language that offers its users an array of potent tools for working with various data structures. One such data structure is the array, which is a collection of elements stored in adjacent memory regions. This article aims to guide you through the process of discovering the location of an element in a Python array, which is a valuable skill for various programming applications. We will define the concept of an "address, " explain the syntax for obtaining it, and present several techniques with accompanying algorithms and actual code samples. By the end of ... Read More
Dice Rolling Simulator is a basic cube that creates a random number when a user rolls it. These programs are frequently employed in a wide range of simulations, games, and even statistical analysis. Python is one of the most often utilized programming languages for making dice simulators. This essay will go over the history, conception, and execution of a Python-Random-based dice rolling simulator. Design and Implementation Designing and building a dice simulator with Python-Random is not too difficult. The programme will produce a random number between 1 and 6, which will be used to mimic the roll of a die. ... Read More
Numerous libraries that offer geolocation services are available in Python, notably the geopy module, which enables programmers to geocode and reverse geocode addresses and places. Calculating the distance between two points is made simpler by the geopy package, which also offers distance calculations between two points. There are several libraries that allow for the manipulation of geographical data in Python, including GeoDjango, GeoPandas, and PyProj. These libraries make it simpler for programmers to manipulate geographic data, such as points, lines, and polygons, making it possible to design applications that call for mapping and spatial analysis. The geopy library can be ... Read More