{"version":"1.0","type":"rich","title":"Pandas fuzzy join","description":"This example shows how to align two Pandas DataFrames with slightly misspelled index labels, producing a joined table where each row pairs a number with its corresponding letter. The code uses `difflib.get_close_matches` within a `map` operation on the second DataFrame’s index to find the closest match in the first DataFrame’s index, then applies `df1.join(df2)` to merge them. The result corrects mismatches like \"too\" to \"two\" and \"fours\" to \"four\", demonstrating a fuzzy-join pattern with Pandas’ built-in join API.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-76097b8d4ddd2e396ba537de1e3d0e67?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}