Json visualization

When dealing with complex JSON response data from APIs, finding specific information can be time-consuming and frustrating. This is especially true when the response includes nested objects, arrays, and image URLs. Scrolling through the JSON response to locate required fields not only wastes time but also increases the risk of errors.Apidog addresses this challenge by providing a programmable method to convert complex JSON response data into an intuitive graphical interface. This feature enhances data search efficiency, improves readability, and minimizes errors. In this blog, we will explore API response data visualization, its benefits, and how you can leverage Apidog's visualizer to streamline your workflow.💡Apidog is a powerful tool designed to streamline the development, testing, and visualization of API responses. It provides a comprehensive platform that allows developers to transform complex JSON or XML data returned by APIs into easily understandable visual formats such as tables, charts, and images.buttonWhat is API Response Data Visualization?API response data visualization involves transforming complex JSON or XML data returned by an API into an easy-to-understand visual format. Instead of sifting through nested objects and arrays in raw data, visualizations present this information in graphical forms such as tables, charts, or images. This process often involves using scripts or tools to parse the raw data and render it into a format that highlights key information clearly and intuitively.Benefits of API Response Data Visualization1. Enhanced ReadabilitySimplified Data Inspection: Visualizations convert complex data structures into clear, visual representations, making them easier to understand and analyze.Quick Identification of Key Information: Visual formats like charts and tables allow users to quickly identify trends, outliers, and key metrics without delving into raw data.2. Improved EfficiencyFaster Data Analysis: Visual representations reduce the time needed to interpret data, enabling faster decision-making and troubleshooting.Streamlined Debugging: Developers can more easily pinpoint issues within API responses by visualizing data, leading to quicker debugging and problem resolution.3. Reduced ErrorsMinimized Human Error: Visual formats decrease the likelihood of misinterpreting data compared to manually parsing raw JSON or XML.Consistent Data Interpretation: Visualizations ensure that all team members view and interpret the data in the same way, promoting consistency and

What is a CSV to JSON Converter? A CSV to JSON Converter is an online tool that transforms CSV (Comma-Separated Values) data into JSON (JavaScript Object Notation) format. JSON is widely used for data interchange and is easier to work with in modern programming languages. How Does the CSV to JSON Converter Work? Using our CSV to JSON Converter is simple and straightforward. Here's how it works: Upload CSV: Select the CSV file you want to convert. Adjust Options: Customize the CSV parsing and JSON output options. Convert: Click "Convert to JSON" to transform the CSV data into JSON format. View Results: Instantly see the converted JSON data. Download: Download the JSON file for further use. Who Can Use This Tool? Our CSV to JSON Converter is designed for a wide range of users, including: Developers: Convert CSV data for use in APIs or applications. Data Analysts: Transform CSV data for analysis or visualization. QA Engineers: Test JSON-based systems with converted data.

Nov 22, 20236 minute readWith so many tools available, how do you select the best JSON viewer for macOS? Join us as we explore the macOS-specific JSON viewer tools. In this post, we'll provide a brief overview of each tool, touching on its standout features, pros, and cons. Together, we'll study their features, strengths, and limits.At first, you'll have a clear comparison table showcasing each tool's efficiency based on processing speed and more. We've ranked these tools by their efficiency in handling large JSON files, listing the most proficient ones first. By the end, you'll be prepared to choose the best JSON viewer for macOS. Let's jump in!Below is a comparison table outlining the capabilities of several JSON viewer tools, specially crafted for macOS. We conducted tests to evaluate their JSON data load performance using a consistent environment.1 This table provides insights into each tool's processing speed, memory efficiency, and best-suited use case.Tool NameFile size processed in 1 minuteMemory Efficiency Ratio (Memory Taken: File Size)Best Suited For1. Dadroit JSON Viewer~ 24 GB1:1Rapid, organized tree views of huge JSON files.2. JSON Query~ 2 GB60:1Viewing and querying JSON data.3. Smart JSON Editor~ 0.365 GB9:1Sophisticated JSON data creation and validation.4. JSON Viewer for macOS~ 0.013 GB310:1JSON visualization and validation.5. JSON Wizard~ 1 MB364:1Viewing, validating, and formatting JSON files.6. Jayson~ 1 MB33:1JSON visualization with drag-and-drop utilities.1. Dadroit JSON Viewer: A Powerhouse for Large JSON FilesDadroit JSON Viewer is recognized as one of the most notable JSON viewer tools for macOS due to its capability to handle large JSON files. Beyond its primary viewing function, it provides users with additional features such as advanced search capabilities and conversion options.ProsProcesses data with remarkable speedSupports other JSON-based formats such as NDJSON (.ndjson) and JSON Lines (.jsonl).Detailed and rapid (10GB/S) searches, including RegexDisplays data in an organized node tree view mannerJoins multiple JSON data files into 1 viewExport to CSV and XMLSupports Windows, macOS, and Linux platformsConsNo built-in JSON editing feature2. JSON Query: Navigating Data with PrecisionJSON Query offers a specialized environment for users aiming for detailed data interrogation. With a foundation built on JMESPath query language, it's more than just a viewer—it's a powerful data exploration tool.ProsAdvanced JSON querying using JMESPathClassic tree viewA range of search-related featuresConsMay not be suitable for users looking for simple JSON viewing.Requires familiarity with JMESPath to leverage its full potential.3. Smart JSON Editor: Crafting JSON on macOS with PrecisionSmart JSON Editor is a macOS application designed to offer JSON editing features. While it presents an array of validation functions, it caters more to users familiar with advanced JSON manipulation.ProsComprehensive editing capabilitiesValidation tools for JSON data accuracyConsMay be challenging for newcomers to JSON editingThe extensive features and interface might not be intuitive for

By default, the world map is displayed. But what if we want to visualize data related to just India. We can select 'India state and territories' in vectormap option.It will display a detailed map of India with the state boundaries now.Similarly, there are other options such as 'USA states' or 'Australia states'.color-schema: to control the color displayed in the visualization as per the ranges. border thickness: to control the line size by which Kibana draws the boundaries in the map.Click to view in HDHow to Create a Kibana Dashboard?A dashboard in Kibana is a collection of various visualizations. Here is an example dashboard.Click to view in HDWe will create a similar dashboard from the visualizations in the above section.Steps to create a dashboardHead to the dashboard section of Kibana and create a new dashboard.Start adding the visualization and saved queries here.That's it! You have created your very own first dashboard now! Save it for future use.Next stepsIn production environments, teams usually try to keep a backup of these visualizations and dashboards in a JSON file for safekeeping.Steps to create a backup file:Go to Kibana's management section.Go to the saved objects tab.Select your visualizations and dashboards from the list.Export them. Kibana will create a JSON file for you and download it to your system.Creating a backup is not enough; we also need to understand importing the objects through the file.Steps to import an object using a backup file:Under the saved objects click on the Import button.Next, select your JSON backup file.

--> --> This procedure shows how to use the REST API to get data out of ThoughtSpot, so you can use it in a webpage, portal, or application.Data retrieved using the Data REST API is returned as JSON (JavaScript Object Notation).Before you can use the Data REST API, you need to enable the JavaScript API (JS API) and authenticate to ThoughtSpot.Use this procedure to construct the URL you will use to call the Data REST API:Sign in to ThoughtSpot from a browser.Navigate to the Liveboard from which you want to get data.If it doesn’t exist yet, create it now.Find the ID number of the object you want to get the data from. Select the More menu icon for the object and select Copy embed link.Copy the ID number from the link shown.Paste it somewhere so that you can use it later to construct the URL to use when calling the REST API.If the object is:LiveboardCopy the identifier that appears after "viz/".Omit the trailing "/".VisualizationCopy the entire identifier that appears after "viz/". This is the visualization ID. This includes the Liveboard ID as well.Note: A visualization is a table or a chart.Construct the URL as follows: For a Liveboard, the URL takes the form: /pinboarddata?id=For a visualization, the URL takes the form: /pinboarddata?id=&vizid=%5B%5DIf you want to apply any filters to the data that will be returned, apply Runtime filters.Now your URL is complete, and you can use it to access the data directly through the HTTP POST method.The Data REST API returns the data formatted as JSON.Retrieve the data from the JSON and display it in your webpage, web portal, or application. Was this page helpful?Give us feedback!

DAX Query ExplorerThe most powerful and intuitive way to visualize and analyze DAX query execution plans. DAX Query Explorer transforms complex query plans into interactive, visual flowcharts that make understanding query execution simple and efficient.FeaturesInteractive Visualization: Transform text-based DAX query plans into interactive, visual flowchartsFlexible Input Formats: Support for both plain text query plans and JSON format exported from DAX StudioNode Type Differentiation: Distinct visual representations for different operation types:Spool Physical Operations (SpoolPhyOp)Iteration Physical Operations (IterPhyOp)Lookup Physical Operations (LookupPhyOp)Scalar Logical Operations (ScaLogOp)Relational Logical Operations (RelLogOp)Collapsible Nodes: Simplify complex plans by collapsing nodes to focus on specific parts of the executionSmart Layout: Automatic node positioning and edge routing for optimal readabilityPlan Sharing: Share query plans with colleagues via unique URLsResponsive Design: Works seamlessly on both desktop and mobile devicesGetting StartedVisit DAX Query ExplorerPaste your DAX query plan into the editor:Either paste the plain text query planOr paste the JSON output exported from DAX StudioClick "Parse Query Plan" to generate the visual representationExplore the execution plan through the interactive visualizationUsageViewing Query PlansThe interface is split into two main sections:Left: Code editor for inputting DAX query plans (accepts both text and JSON formats)Right: Interactive flowchart visualizationInput FormatsDAX Query Explorer supports two input formats:Plain Text: The standard text output of a DAX query planJSON Format: The JSON export from DAX Studio, containing both physical and logical query plan rowsNode InformationEach node in the visualization contains important information about the operation:Operation type and nameNumber of records processedKey columns and value columnsAdditional operation-specific detailsSharing PlansClick the "Share Plan" button in the top right cornerA unique URL will be generated and copied to your clipboardShare the URL with others to let them view the same query planWhy DAX Query Explorer?Understanding DAX query plans is crucial for optimizing Power BI and Analysis Services performance. DAX Query Explorer makes this process intuitive by:Converting complex text-based plans into clear visual representationsHighlighting relationships between operationsMaking it easy to identify bottlenecks and optimization opportunitiesFacilitating collaboration through plan sharingContributingWe welcome contributions! Please feel free to submit issues and pull requests.