1.2. Why Learn To Code?¶
Many might think that every data analyst’s career starts with learning the ins and outs of spreadsheets, but spreadsheets are not the only way to start off on your journey. We start with learning to code for a few reasons.
First, as an analyst, every program you use is allowing you to communicate instructions to a machine. Whether it is writing Python code or using a drag-and-drop menu in Tableau, you are asking a machine to perform certain necessary tasks to help you achieve a goal. Code is the undercurrent of all of these programs. By learning to code first, you are learning the most universal aspect of all of the tools you will use throughout your career. With this particular knowledge, you will also be better prepared to adapt to the needs of your workplace. Not every company uses Tableau and Azure Data Studio. Some may insist you use a code-centric tool like Matplotlib for visualizations.
Through learning to code, you will also gain confidence in handling errors. Errors come up when working with any software program and they also come up when handling data. All it can take is one typo to throw off your analysis of a dataset.
You will also learn concepts that you will use throughout the course as you dive deeper into the world of data. One such concept is data types. Without spoiling too much, data types matter immensely to data analysts. Datasets are not just numbers. They can also holds names, dates, and other information of various different types and data analysts need to be able to work with all of the different types of data. No matter what tool you are using at the moment in the course or throughout your career, you will need to take into account data types when looking at a dataset.
Now that you are ready to learn how to code, let’s focus in on why we are starting with Python.