Dropping data

In the previous recipes, we introduced how to revise and filter datasets. Following these steps almost concludes the data preprocessing and preparation phase. However, we may still find some bad data within our dataset. Thus, we should discard this bad data or unwanted records to prevent it from generating misleading results. Here, we introduce some practical methods to remove this unnecessary data.

Getting ready

Refer to the Converting data types recipe and convert each attribute of imported data into the proper data type. Also, rename the columns of the employees and salaries datasets by following the steps from the Renaming the data variable recipe.

How to do it…

Perform the following steps to drop an attribute from the current dataset:

1. First, you can drop the last_name column by excluding last_name in our filtered subset:

   > employees <- employees[,-5]
   

2. Or, you can assign NULL to the attribute you wish to drop:

   > employees$hire_date <- NULL
   

3. To drop rows, you can specify...