Showing a Dataframe in a code cell can go a long way to understanding how your code operates.
This capability reinforces the use of Jupyter Notebook in a prototyping workflow when you are attempting to confirm that your workflow is doing what it needs to do at each step of the way. This is extremely useful because you can view the state of your data (and the effect of all the actions your code is performing on your data) as each step of your logic executes. Jupyter Notebook allows you to visualize these tables at any point in your notebook. The core data object is a Dataframe, which is essentially an in-memory table that allows powerful indexing operations. Pandas (Python Data Analysis Library) provides high-performing and easy-to-use data structures that allow you to work with large amounts of data extremely fast. Many Integrated Development Environments (IDEs) allow you to do this in several ways, but I’ve found Jupyter Notebook’s concept of a “code cell” to be the most intuitive approach for prototyping logic and sequential code. This allows a Python user to quickly test a specific step in a sequential workflow without re-executing code from the beginning of the script. This is mainly thanks to the feature where code is written into independent cells, which can each execute independently from the rest of the code. Jupyter Notebooks are extremely useful when you do not have a defined final process and are still in the prototyping phase of your scripted workflow. As a GIS user, I have personally found Jupyter Notebooks to be extremely useful for the following three reasons: 1. Jupyter Notebooks have gained tremendous popularity in the Python data science community over the past years for a variety of reasons. The term “notebook” is very applicable, since the tool allows you to write snippets of self-contained executable code (named “cells”), note each procedure, and even visualize data you are working with at any step of the way. Jupyter Notebook is a powerful tool that allows Python users to create and share documents containing live code, visualizations, explanatory text, and equations.
0 kommentar(er)
