Some common mistakes to avoid when using PairPlot in Python

When working with pairplot in Python to visualize a dataset, some common mistakes can occur and a few of them are listed below along with a sample code for each.

1. Not specifying the "data" parameter:

One common mistake is not providing the correct dataset to the pairplot function. This can happen if you forget to pass the data parameter or provide the wrong variable name.

2. Specifying all of the data together:

If your dataset has a lot of features and input variables, then it might not be suitable to use the complete dataset for visualization. It is computationally expensive and can also lead to bad results. To solve this, you can use the vars parameter and specify only a few features that you want to visualize.

3. Forgetting to import the "matplotlib" library:

Since pairplot is present in the Seaborn library, a common mistake can occur which involves forgetting to import the matplotlib library. This library is useful as you commonly would use to display any kind of visualization even if that visualization belongs to the Seaborn library.