![]() ![]() Welcome to, a free service hosted by the University of Ruse Index of /pclinuxos/pclinuxos/srpms/SRPMS.pclos/ Index of /pclinuxos/pclinuxos/srpms/SRPMS.pclos/ ![]() Whatever the case might be, you now know how to take full control of your Pandas version.Welcome to Open Source Software Mirror - hosted by University of Ruse That’s likely the case with Pandas 2.0 since there are major changes when compared to the previous releases. Or maybe you just want to install the most recent development version inside a virtual environment. These typically have the library name followed by a version, since you don’t want a recent package update to break something in your production code. You probably don’t want to install a deprecated version of the library on your system, at least not when working on new products, so what’s the point of this article? Well, maybe you’re planning on deploying your project and need a requirements.txt file. ![]() ![]() It looks like the correct version was installed, so we can mark our job here as done. Image 4 - Testing Pandas specific version installation (Image by author) Image 3 - Installing Pandas 1.3.4 with Anaconda (Image by author)Īnd now open up the Python shell, import Pandas, and print its version: ![]()
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