Lux: Excellence in Data Analysis and Visualisation

Data is sacred in today's world, and Python libraries like Lux make data analysis and visualisation so much easier.

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Data analytics and visualisation are key components of any real-world application. The analysis of historical data as well as predictive evaluations is crucial and helps organisations make strategic decisions. Hidden patterns that emerge as a result of data engineering help companies to evaluate customer feedback, customer leads, social media messages, e-commerce shopping patterns, and so on.

The applications and use cases of data engineering include predictive maintenance, customer segmentation, fraud detection, demand forecasting, sentiment analysis, recommender systems, speech recognition, image classification, autonomous vehicles, drug discovery, medical diagnosis, energy consumption prediction, supply chain optimisation, financial risk modelling, anomaly detection, natural language processing, smart city analytics, climate modelling, etc.

Table 1 lists the free and open source libraries for data analytics that can be programmed in different languages depending upon the use case and application.

Python offers a number of free and open source libraries that are dedicated to data visualisation and plotting. Table 2 lists these.

Using the Lux library for advanced visualisation in minimal coding