Introduction to Pandas With SQLite

In this segment, you will learn how to use another very-well-known Python library: Pandas. Note that Pandas is not a part of the key takeaway from this case study, as you will be learning about it in a lot more detail in the next course. However, as we go deeper into the case study, you will see that it will become very difficult if we have to carry out all of it using SQL, especially when the same outcome can be achieved with a simple code using the Pandas library.

In the forthcoming video, Favio will introduce you to Pandas and an interesting data structure known as a dataframe. Let us go ahead and watch the video.

So, in the video, you learned how to create a dataframe out of a database using Pandas. You also learned how to get the output of an SQL query in the form of a dataframe. 

Now, as you saw in the earlier segments, the data that we have at hand exists in the form of csv files. In the next video, Favio will show you how to import data from csv files directly into Python with the help of Pandas. Let us go ahead and watch the video.

So, in the video, you saw how we can convert data in the form of a csv file to an SQLite database. We will use this later when we will need to extract the actual customer churn data and create a database.

Moving on, in the next segment, Favio will show you how to write a simple Python logic, which you can later use for printing all the columns in each table of the database.