Loading the Exercise 1 data using Python

For this exercise, use the same iris.csv file from the previous chapter and open it using any spreadsheet software. We’ll be using Google Sheets in this book to show you how to edit spreadsheet files. In this chapter, you’ll learn how to deal with missing values. The Iris dataset is preprocessed in its original form, so it doesn’t have any missing or invalid values. For this exercise, missing values will be artificially introduced.

Follow these steps to complete this exercise:

1. Open the iris.csv file.
2. Randomly delete (as shown in Figure 3.4) some of the cells (6 for this example) for the sepal_length row or other columns.
3. Randomly delete some of the cells for the petal_length row.
4. In the petal_length row, add Nan as a term.
5. Save the file as Iris_m.csv. You’ll see the output on the next page:

Figure 3.4 – The Iris dataset as a spreadsheet

You can use...