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With a wide selection of chart types available, Excel is a potent tool for data analysis and visualisation. While making separate charts for various data sets is helpful, there are times when you might wish to group several charts together on a single chart sheet. Combining charts can make it easier to compare and analyse data trends, provide you a thorough perspective, and improve the overall visual impact. In this article, we'll look at a variety of Excel display strategies for numerous charts on a single chart page. This post will walk you through the step−by−step process of producing and ... Read More
Pie charts are a common and useful approach to show data distribution; however, it can occasionally be difficult to identify each data point precisely. Leader lines are helpful in situations like these. Leader lines make it simpler for readers to recognise and comprehend the values shown in the chart by linking the data labels to their appropriate data slices. You will be guided step−by−step through the process of adding leader lines to your Excel pie chart in this tutorial. This tutorial will provide you with the knowledge and abilities you need to improve the clarity and visual attractiveness of your ... Read More
The most basic difference between classification and clustering is that classification is used with supervised learning technique, whereas clustering is used with unsupervised learning technique. In classification, the computer is given a label to use in classifying new observations. For the label verification in this case, the machine requires thorough testing and training. Classification is therefore a more intricate procedure than clustering. In contrast, clustering is an unsupervised learning method that groups data based on similarities. Here, there is no need for training because the machine learns from the already−existing data. In this article, we will discuss the important ... Read More
Word embeddings play a crucial role in Natural Language Processing (NLP) by providing numerical representations of words that capture their semantic and syntactic properties. These distributed representations enable machines to process and understand human language more effectively. In this article, we will delve into the fundamentals, popular embedding models, practical aspects, evaluation techniques, and advanced topics related to word embeddings in NLP. Fundamentals of Word Embeddings Word embeddings are dense, low-dimensional vectors that represent words in a continuous vector space. They aim to capture the meaning and relationships between words based on their context in a given corpus. Instead ... Read More
HTML tags are used to design the skeleton of websites. We pass information and upload content in the form of strings enclosed within the tags. The strings between the HTML tags determines how the element will be displayed and interpreted by the browser. Therefore, the extraction of these strings plays a crucial role in data manipulation and processing. We can analyse and understand the structure of the HTML document. These strings reveal the hidden pattern and logic behind the construction of a webpage. In this article, we will be dealing with these strings. Our task is to extract the ... Read More
Python strings are sequence of characters that represent information or data. A normal string can contain various characters that are enclosed within single or double quotes but an Alphanumeric string only consist of digits and letters. Both alphanumeric and non-alphanumeric strings are used and applied in various scenarios including password protection, data processing and validation, formatting etc. Specific patterns can be identified and extracted. We can also provide different combinations using these types of strings. We will perform an operation based on these strings. Our task is to extract a string till first non-Alphanumeric character is encountered. Understanding the ... Read More
A python dictionary is a data structure that can be used for numerous operations making it a prolific programming tool. It stores data in the form of key-value pairs i.e., each data can be labelled with a unique key. Keys in dictionaries are identifiers that are associated with different values, these values can be accessed, modified and deleted. Based on the task, keys can be sorted and extracted in different orders. In this article, we will be discussing a similar concept of extracting N largest dictionaries keys. We will operate on these unique keys and extract the relevant data. ... Read More
Pattern recognition is an important programming concept. It allows us to retrieve specific data that satisfies a particular condition or match a particular sequence. This principle is helpful in various fields including language and image processing. String matching helps us to extract meaningful information from a large collection of data. In this article, we will be discussing a similar concept of extracting mesh matching strings from a given list of strings. Mesh matching focuses on the extraction “similar” strings of equal length, let’s discuss this problem in detail. Understanding the Problem The main concept is to extract similar ... Read More
Dictionaries in python are data structures that store data in the form of key-value pairs. Each key is unique and it is associated with different values. A dictionary helps us to access and retrieve data efficiently allowing a programmer to build an optimized code. Specific key-value pairs can be extracted from a given dictionary based on different requirements. This selective item extraction helps us to produce a dictionary consisting of relevant information. In this article, we will be discussing a similar concept of item extraction from a dictionary based on a reference “substring”. Understanding the Problem We ... Read More
If you work with data in Excel, you may often need to analyse trends and patterns within your data. One important metric to consider is the number of peaks, which refers to the maximum values in a set of data. Peaks can help you identify changes in trends, detect outliers, and make important decisions. Counting the number of peaks in a column of data can be a useful technique for analysing data. However, manually identifying peaks in a large set of data can be a time-consuming and error-prone task. Fortunately, Excel provides several tools that can help you quickly and ... Read More