![]() At this point you’re ready to perform the GDAL installation. You should see (pygdal), or your environment’s name, to the left of the current working directory in the command prompt. Make sure your pygdal environment has been activated. conda activate pygdal Install GDAL with conda install Now activate the environment using conda activate env-name. Here, pygdal is the name of the environment that was created. To create an anaconda environment, enter the following code. I’ve run into trouble installing GDAL to the base environment, but haven’t had issues when I’ve created a new conda environment. Now, make sure you’re installing GDAL to an environment. If using Windows, you’ll need to have the Anaconda distribution directories added to your path variable or open the Anaconda Prompt (recommended). ![]() If you’re using Mac or Linux this will probably be your regular terminal window. Once you get GDAL installed, check out our tutorial to get started using GDAL with Python. You can check out the video at the end of this article for a demonstration. This guide will demonstrate how to successfully install GDAL from the conda-forge channel to an Anaconda ( conda) environment. ![]() There are two reliable ways to install the GDAL python package: from the conda-forge channel using the conda installer or using pip to install a precompiled wheel. However, it is notoriously difficult to install. GDAL is a powerful package with a lot of functionality. The Geospatial Data Abstraction Library (GDAL) is a fundamental package for spatial analysis with Python. ![]()
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