To call the resulting output from the pandas profiling library “basic” is a monumental understatement. !jupyter nbextension enable -py widgetsnbextension The 'Basics': Pandas Profile Reports Side note: The Jupyter widget extensions can be run in a Jupyter notebook as well. The widgets library, also installed during the pandas profiling installation, is now enabled. Jupyter nbextension enable -py widgetsnbextension To enable this functionality, prior to opening Jupyter notebook, run the following command in your terminal: Jupyter notebook includes a widgets extension that provides some visual feedback as the report is being created. When creating the profile report, it takes a little time for the report to be generated. Step 2: Including Widgets for Your Jupyter Notebook Now your version of pandas is up to date. Pip install -upgrade -force-reinstall pandas Head to your terminal again and run the following command to 'force' your existing pandas to be updated. If this happens, the resolution is to upgrade the existing version of pandas with the most recent version. If you have an older version of pandas installed, pandas profiling may throw an error. Important Note: Because the pandas profiling library relies on pandas, your version must align with the version of pandas used by the pandas profiling library. The conda installation will take care of installing everything required. Using Anaconda’s terminal, run the following command:Ĭonda install -c conda-forge pandas-profiling If you decided to install the Anaconda suite of applications to work with Python, you will install the pandas profiling library via the conda package installation process. In one fell swoop, you will have everything you need to create a profile report. As the pip installation runs, you will notice that it will install a LOT of packages, including pandas, Jupyter notebooks, and seaborn just to name a few. The pip installation process will include everything you will need. From your terminal (Mac) or cmd (Windows), run the following command: If you are using Python as a stand-alone application on your machine, you will use the package installer, pip, to install pandas profiling. The only thing you will need to consider is how you wish to install pandas profiling. The pandas profiling installation will take care of all the heavy lifting for you. If you are new to Python or have never installed pandas, do not fear. Java - Uses, Performance, Learning Getting Started: Installing Pandas There is no steep learning curve or required deep understanding of multiple packages by using pandas profiling. The pandas profiling library can create, in a few lines of code, a rich and interactive suite of exploratory data analysis ( EDA) tables and visualizations. This becomes especially relevant when all you want is to quickly gain some initial insight into the data. However, it can be daunting to learn pandas, with their related data analysis packages (matplotlib, seaborn, etc.) and all their coding methods and attributes. Python’s third-party package, pandas, has been a mainstay for data analysts and data scientists for quite some time.
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