I followed the customization method to avoid setting up environment variable.Īs below figure 5 shown, the Customize installation location, where make sure you put the installation location folder C:\Python\Python39. ![]() Make sure to choose 'Customize Installation' and check mark 'Add Python 3.9 to PATH' as shown in figure 4. Now double click the executable file to initiate the installation process. Now next step is to create a 'Python' folder under the C: drive, we will use this folder as installation location at later step.įind out the downloaded executable file, I have saved the executable file under Downloads folder (shown in below figure 3). You can download the executable file and save in any location at your computer. Please choose the version as per your computer Operating system. I have chosen 'Windows x86-64 executable installer' for my Windows 64 bit OS. Please follow this URL and choose right version to install. Python is a prerequisite for running a Jupyter notebook, so we need to install python first. This post will describe the step by step installation process of Jupyter notebook. The Jupyter Notebook can be used for data cleaning and transformation, data visualization, machine learning, statistical modeling and much more. Well, that's how I found a Jupyter notebook can be useful to compare two. ![]() At the beginning I was manually comparing them then I thought there must be a tool to do that. parquet were created from two different sources, the outcome should be completely alike, schema wise. This is mainly a schema comparison, not a data comparison. One of the projects I was working required a comparison of two parquet files. Whether you work as a Data Engineer or a Data Scientist, a Jupyter Notebook is a helpful tool.
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