In the last article , we introduced statements and indentation in Python. Next, let’s discuss commenting in Python. Comments are descriptions of the code under consideration. So we can write one or more lines of explanation. There can be times when you need to write some long and complicated code for a task. After it is complete, you might save the file somewhere, but when you refer to the code sometime in the future, let’s say, after three or four months, you may not be able to understand the code you have written yourself! To help yourself and anyone going through your code, in the hope of understanding its utility, you should generously use comments to clarify the written code. Commenting is necessary, especially for the complicated functions you might have created for a specific task. There are a few ways to declare a comment inside Python. The easiest way is to use a hash symbol (#). When we use the hash symbol inside our code, the python interpreter igno...
In the last article , we introduced the software installation process required for data science in python. In this blog, we will begin creating our first project in Pycharm. We can open Pycharm and click on the plus sign to create a new project, as shown below: Now, as soon as you click on create the project button, you will go to another screen where you have to mention the desired project name, as shown below: The default project name is ‘untitled’, as shown in the image above. Next, we see a small triangle shape symbol under the “Location” part of the screen. When we click the triangle, Pycharm provides us with many options, as shown below: In the options above, we see one titled “New Environment Using”. If we click the drop-down menu, we see one of them is “Conda”, which is short for “Anaconda”. We need to select this option before clicking on the Create button to be sure that we are creating the new environment using anaconda distribution. One important thing you ...
Let’s discuss how someone interested in coding and data science can begin their journey. You see many people learning Python and data science. Once they have their data analyst or data scientist jobs, they lead a comfortable lifestyle thanks to the value their skillset generates for society, directly allowing the individual to earn a lot of money. You decide to give it a try, and you get yourself a laptop. Now, the questions you get are something like the following: Where do you begin? Which course do you take? These are critical questions to be answered if you want to reach your desired goal. With the available options on the internet, you might feel a little dizzy just going through choices of the various courses. This article is my attempt to make your journey a little more comfortable. I will focus on the Python language, but be aware that we have many coding languages to choose from for learning this skill set. We will begin by installing the required software for learning d...
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