#Pd drop duplicates how to

Typically, the columns of a dataframe are variables, and the rows typically record individual data records. Pandas dataframes store data in a row-and-column format. Let’s look more carefully at dataframe structure. We use dataframes to store certain types of data, and we use Pandas techniques to manipulate dataframe data. (Remember: the drop duplicates method operates on Pandas dataframes.)Ī dataframe is a data structure in Python that’s available in the Pandas package. Dataframes Store Python Dataįirst, let’s quickly review what a dataframe is. This will give you some context, and help you understand exactly what this technique does, and why we might use it. I’ll show you some examples of this in the examples section, but first, I want to quickly review some fundamentals about Pandas and Pandas dataframes. Stated simply, the Pandas drop duplicates method removes duplicate rows from a Pandas dataframe. Having said that, if you really want to know how this technique works, you should probably read the whole tutorial.Īn Introduction to Pandas Drop Duplicates

If you need something specific, you can click on one of the links above.

#Pd drop duplicates how to

Examples: How to drop duplicate rows from a dataframe.An Introduction to Pandas Drop Duplicates.You can click on any of the following links, and it will take you to the appropriate section in the tutorial. The tutorial will explain what the technique does, explain the syntax, and it will also show you clear examples. This tutorial will show you how to use Pandas drop duplicates to remove duplicate rows from a dataframe.