How to Boost Pandas Speed And Process 10M-row Datasets in Milliseconds
<p>“Great… another article on how to make Pandas <em>n</em> times faster.”</p>
<p>I think I have said that countless times for the past three years I have been using Pandas. The most recent one I saw said, “make Pandas 71,803 times faster”.</p>
<p>But I won’t give you that kind of promise. I will just show you how to use Pandas in the fastest way possible. Because you can’t speed up something which is already fast.</p>
<p>Doesn’t that make sense?</p>
<p>Let me ask you this. Which hand do you use when I say, “Touch your right ear.” Of course, the right hand. You wouldn’t touch your right ear by putting your left hand over your head. That would be weird.</p>
<p>Well, using functions that the Pandas documentation explicitly states as <strong>slow </strong>instead of the fastest methods would also be weird.</p>
<p>That’s why this article will show you the best practices of some of the most common data manipulation operations in Pandas. You can even consider these best practices as “common sense” because that’s how the maintainers of Pandas intended their library to be used.</p>
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