Effortless Data Cleaning with Pandas Rename
When handling messy datasets, clear and consistent column names make all the difference. The pandas rename method provides a straightforward way to update column and index labels in your DataFrame. By passing a dictionary mapping old names to new ones, you can instantly transform confusing labels into meaningful identifiers. Beyond simple mappings, the method also supports function-based renaming, which is useful when you need to apply formatting rules such as converting names to lowercase or adding prefixes. You can choose between returning a new DataFrame with updated labels or making the change directly in place using the inplace=True parameter. In addition, pandas rename isn’t limited to columns—it also allows renaming of index labels, ensuring consistency across your entire dataset. For data cleaning, preparation, and analysis, this feature is essential.
Learn more with practical examples at Vultr’s documentation: https://docs.vultr.com/python/....third-party/pandas/D