![]() ![]() To be clear, an index is only sort of like a column, but properly speaking, it’s not actually one of the columns of a DataFrame. One important feature of the DataFrame is what we call the “index.”Įvery Pandas DataFrame has a special column-like structure called the index. It’s just a row-and-column structure that holds data and enables us to perform analyses on that data. Variables are along the columns, and observations (i.e., records) are down the rows.Īt a high level, a Pandas DataFrame is a lot like an Excel spreadsheet. A quick review of Pandas DataFramesĪ Pandas DataFrame is a data structure in Python.ĭataFrames have a row-and-column structure. ![]() With that in mind, let’s review Pandas DataFrames and DataFrame indexes. Once you know that, we’ll be ready to talk about the reset_index method. You really need to understand what an index is, why we need them, and how we set indexes in Pandas. To understand the Pandas reset index method, you really need to understand Pandas DataFrame indexes. Having said that, if you’re new to Pandas, or new to using Pandas DataFrame indexes, you should probably read the whole thing. ![]() You can click on one of the following links, and the link will take you to the appropriate section in the tutorial. It will explain the syntax of reset_index, and it will also show you clear step-by-step examples of how to use reset_index to reset the index of a Pandas DataFrame. This tutorial will show you how to use the Pandas reset index method. ![]()
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