The library to do so in Python is Pandas which is a key part of our work. It is a flexible and easy-to-use open-source data analysis and manipulation tool. 

Like matrixes, data frames also have rows and columns but can hold different types of variables in each column.

Think about it for a moment. The power! This way, we can record any observation in the world. Any observation will have different attributes we associate with it. For instance, flowers can be of different types and colours. With data frames, we can record each observation of flowers by recording it in rows and assign to the columns the various features we observe, like colour, type, etc. This way, the whole world is for us to record in data frames!

In the notebook in Google Colab, we will look at how we can recreate the data from the last session in the NumPy array.

Check if you got it!