What are some popular tools and software for data visualisation?

There are several popular tools and software available for data visualization that cater to different needs and skill levels. Some of the most widely used ones include:

1. Tableau: Tableau is one of the leading data visualization tools that offers a user-friendly interface and a wide range of features. It allows users to create interactive dashboards, charts, and maps, and supports various data sources.

2. Microsoft Power BI: Power BI is a powerful business intelligence tool that enables users to create visually appealing and interactive reports and dashboards. It integrates well with other Microsoft products and offers advanced analytics capabilities.

3. QlikView: QlikView is a self-service data visualization and discovery tool that allows users to explore and analyze data from multiple sources. It offers drag-and-drop functionality and provides interactive visualizations for better data understanding.

4. D3.js: D3.js is a JavaScript library that provides a flexible and powerful framework for creating custom data visualizations. It allows users to manipulate data and design interactive charts, graphs, and maps using HTML, CSS, and SVG.

5. Google Data Studio: Google Data Studio is a free tool that allows users to create interactive dashboards and reports using data from various sources, including Google Analytics, Google Sheets, and BigQuery. It offers collaboration features and easy sharing options.

6. Python libraries: Python has several libraries dedicated to data visualization, such as Matplotlib, Seaborn, and Plotly. These libraries provide a wide range of plotting options and customization capabilities, making them popular among data scientists and analysts.

7. Excel: Microsoft Excel is a widely used spreadsheet software that also offers basic data visualization capabilities. It allows users to create charts, graphs, and pivot tables to visualize and analyze data.

8. R programming language: R is a popular programming language for statistical computing and graphics. It has various packages, such as ggplot2 and plotly, that provide extensive data visualization capabilities.

These are just a few examples of the popular tools and software available for data visualization. The choice of tool depends on factors such as the complexity of the data, the desired level of interactivity, and the user's technical skills and preferences.