PrintThe pandas package provides high-performance data structures and analysis tools, in particular for working with tabular data based on a fast and efficient implementation of a data frame class. It also allows for reading and writing data from/to various formats including CSV and Microsoft Excel. In the following, we show you some examples illustrating how to perform the most important data frame related operations with pandas. Again, we can only scratch the surface of the functionality provided by pandas here. Resources provided at the end will allow you to dive deeper if you wish to do so. We recommend that you start a new Jupyter Notebook and use it to try out the examples from this section for yourself. Use a new code cell for each of block of code you will encounter on the following pages.