![]() Once you found the graphic file you want to enhance, you can either right-click it to view the available options, or you can use the displayed buttons and icons. ![]() Moreover, you can also examine its corresponding EXIF data, such as camera model, exposure time, focal length, and so on.ĭouble-clicking an image opens it in a dedicated tab, where you can perform various editing operations (multiple pictures can be opened in separate tabs). ![]() The main function is that of image explorer, and you only need to navigate to a folder of your choice to preview thumbnails for all supported extensions.Ĭlicking an item displays a wide range of information about it, including a histogram and its properties. Whatever the case might be, you now know how to take full control of your Pandas version.XnView MP stands for XnView Multi-Platform and it packs all the functions provided in the classic version of XnView while also providing increased performance and speed capabilities. 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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