In the context of this exercise, what else does Pandas let us do?
Pandas provides a lot of useful features and functionality to work with data.
One of the most useful features of Pandas is that it provides objects known as Dataframes, which are very similar to 2D arrays of data or database tables. Dataframes are a collection of objects named “Series”, which are individual columns.
With Pandas and its dataframes, you can perform useful functions. As shown in the exercise, you can easily load data from a CSV file and store it as a variable in the form of a dataframe. You can also write to and create new files just as easily.
In addition, you can modify the shape of these dataframes by pivoting, add or remove columns from a dataframe, or merge different dataframes together.
Furthermore, you can utilize some of built-in methods that dataframes provide, such as the
df.mean() methord, which will return the mean value of all the columns, or
df.max(), which will return the highest value of each column of the dataframe.
Because of these reasons, and many others, Pandas can be a very indispensable tool for data analysts.