6 Pandas Mistakes That Silently Tell You Are a Rookie
<h2>Introduction</h2>
<p>We are all used to the big, fat, red error messages that frequently pop up while we code. Fortunately, people won’t spot it because we always fix those errors. But how about the mistakes that give no errors? These are the trickiest, but the pros could easily call them out.</p>
<p>These mistakes are not related to the API or syntax of the tool you are using but are directly associated with best practices and how much time you spend on a tool. Today, we are here to talk about six of such mistakes that come up often among beginner Pandas users, and we will learn how to solve them.</p>
<h2>1. Using Pandas itself</h2>
<p>It is kind of ironic that the first mistake is related to actually using Pandas for certain tasks. Specifically, today’s real-world tabular datasets are just massive. To read them into your environment with Pandas would be a huge mistake.</p>
<p>Why? Because it is so damn slow! Below, we load the TPS October dataset from 2021 with 1M rows and ~300 features, taking up a whopping 2.2GB of disk space.</p>
<p><a href="https://pub.towardsai.net/6-pandas-mistakes-that-silently-tell-you-are-a-rookie-f075c91595e9"><strong>Read More</strong></a></p>