Analyzing data also requires graphing the data or the results from the analysis performed. Many libraries in Python provide useful tools for visualization, but the plots produced are static. The Pandas Bokeh library is a great alternative for creating interactive plots and including them in web projects. Let’s find out how to use it and the results we can achieve through some examples.
Pandas is the most used library by data scientists to analyze data. But if you are not an expert programmer or simply want to explore your data in a simple and intuitive way you can use PandasGUI. This is a library that allows you to view and interact with Pandas dataframes with a simple mouse click.
Nowadays, data processing and analysis is increasingly required within web applications. Unfortunately, the required execution time can sometimes be too large to handle requests asynchronously. In this tutorial we discover how to use Celery in a Django project to create asynchronous tasks for our needs.
Neo4j is the leader in graph databases. Through Cypher queries, it is possible to optimally manage a graph representation of our data and discover interesting correlations between them. Let’s find out how to use it with some simple query examples and some advanced use case suggestions.
Choosing a web framework for developing a web application is always important. The best Python frameworks are, according to developers, Django and Flask. Let’s find out their peculiarities and try to understand which one is the best according to the needs of our project.