7.84 Seconds to Reset Index: Discover the Fastest Method in Pandas

In the world of data manipulation with Python’s Pandas library, resetting the index of a DataFrame can be done in several ways. The `reset_index` function is the go-to method, allowing users to replace the existing index with a default RangeIndex. If you don’t want the old index saved as a column, you can use `df.reset_index(drop=True)`. Alternatively, assigning a new index directly with `df.index = pd.RangeIndex(len(df.index))` or `df.index = range(len(df.index))` can be faster. Performance tests show that setting the index with `pd.RangeIndex` takes about 7.84 seconds per loop, significantly quicker than other methods. Moreover, many Pandas functions like `drop_duplicates()`, `sort_values()`, and `dropna()` include an `ignore_index` parameter that, when set to `True`, automatically resets the index. This feature simplifies operations when modifying DataFrames.

Source: stackoverflow.com