Pandas Profiling is a Python library for data exploration and visualisation. The library creates interactive HTML reports and dashboards that help users to quickly explore, analyse and view datasets. It is based on the popular library Pandas and provides extended functionality for summarising data, including generating advanced visualisations.
The Pandas Profiling library is designed to quickly generate concise summaries and reports about datasets. It uses visualisations and analytics to quickly generate summary statistics and provide useful insights into the data. It is a useful tool for data exploration and machine learning.
The library includes pre-defined visualisations, such as histograms, line plots and scatter plots. It also includes options to customise visualisations in detail and create interactive dashboards. It provides detailed summary statistics and compares results from different statistical distributions.
The library also includes statistical models and machine learning algorithms to help users identify patterns and correlations in the datasets. It also includes features for anomaly detection and outlier detection.
In addition, the library has features for sharing and exporting reports, allowing users to share findings with colleagues and other stakeholders. This makes it easier to communicate results and collaborate on data analysis tasks.
Overall, Pandas Profiling is a powerful and versatile library for data exploration and visualisation. It is a useful tool for quickly gaining insights into datasets and helping to identify areas for further exploration and machine learning tasks.
