![]() In many cases, using Panel can turn projects that used to take weeks or months into something you finish on the same day you started, creating a full Python-backed deployed web service for your visualized data in minutes or hours without having to run a software development project or hand your work over to another team.A histogram is used to summarize discrete or continuous data. Panel thus helps support your entire workflow, so that you never have to commit to only one way of using your data and your analyses, and don’t have to rewrite your code just to make it usable in a different way. That way you can easily switch between exploring your data, building visualizations, adding custom interactivity, sharing with non-technical users, and back again at any point, using the same tools and the same code throughout. Panel lets you move the same code freely between an interactive Jupyter Notebook prompt and a fully deployable standalone server. The same objects can then be reused in more complex combinations to build more ambitious apps, while always sharing the same code that works well on its own. Panel objects are reactive, immediately updating to reflect changes to their state, which makes it simple to compose viewable objects and link them into simple, one-off apps to do a specific exploratory task. Dashboards reporting key performance indicators (KPIs) and trends.Control panels for simulations or experiments. ![]()
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