{ "info": { "author": "Michael Chapman", "author_email": "chapman.michael.c@gmail.com", "bugtrack_url": null, "classifiers": [], "description": "# Sankeyfy - Data wrangling for easy Sankey Visualizations\n\nThe Sankeyfy package aims to simplify the creation of a Sankey\nvisualization through a straightforward function call. Simply\nrun the \"sankeyfy\" function on your dataframe, and it will output\nthe necessary dataframes for a Sankey chart.\n\nI built this for specifically for use with the **Plotly** API,\nbut this should also be useful for its sources or other D3 libraries.\n\nThe function accounts for the following scenarios, and attempts\nto leverage sensible default behavior (but feel free to give feedback \nor contribute!):\n\n1. *Default Scenario:* **Pre-aggregated format**\n * Input is a table of categorical variables/columns with a \n single aggregate column (counts/count distinct, etc.)\n\n2. **Raw Format**\n * Input is a raw table where each row is an observation and\n the columns are all categorical variables.\n * Currently assumes there is a unique id field, will add default\n functionality for this later\n\n\nPlease feel free to give me any feedback or contribute with a PR,\nand hopefully this saves your some time trying to build out some cool\nSankey visuals!\n\n\n## To Do:\n\n1. DONE - Create Default NULL behavior as an option (Fill with an \"unknown\" category that you can feed the value for)\n2. 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