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output:
                      Product    Price    Quantity
                 p1   Bread      20       2
                 p2   Milk       60       5
            We may also retrieve Product, Price, and Quantity for first five purchases using slicing of the form first_label:
            last _label:integerIncrement (first_label and last _label inclusive) as follows:

             >>> groceryDF.loc['p1': 'p5', ['Product', 'Price', 'Quantity']]
            output:
                      Product      Price    Quantity
                 p1   Bread        20       2
                 p2   Milk         60       5
                 p3   Biscuit      20       2
                 p4   Bourn-Vita   70       1
                 p5   Soap         40       4
            Similarly, we may retrieve Product, Price, and Quantity for the three purchases p1, p3, p5, as follows:

             >>> groceryDF.loc['p1': 'p5':2, ['Product', 'Price', 'Quantity']]
            output:
                      Product      Price    Quantity
                 p1   Bread        20       2
                 p3   Biscuit      20       2
                 p5   Soap         40       4
            2.6.3 Setting Row Indexes

            Sometimes it is convenient to use the contents of a column (often the first column) in a spreadsheet as row indexes.
            For example, in the file Grocery.csv, the first column comprises the products purchased by a customer. We may
            achieve this by setting the first column as index, while reading the csv file into a DataFrame:
             >>> import pandas as pd
             >>> groceryDF = pd.read_csv('Grocery.csv', index_col=0)
             >>> print(groceryDF)
            output:
                              Category  Price  Quantity
                 Product
                 Bread            Food     20         2
                 Milk             Food     60         5
                 Biscuit          Food     20         2
                 Bourn-Vita       Food     70         1
                 Soap          Hygiene     40         4
                 Brush         Hygiene     30         2
                 Detergent   Household     80         1
                 Tissues       Hygiene     30         5
            In the above statement, we set index_col = 0 to use the first column as the row labels. It would be interesting to
            know that the default value of keyword argument index_col is set to None, which means that row indexes must
            begin with 0 and no column is to be used as the row labels.

            Alternatively, we may use the set_index() method to explicitly set a column as the index after reading a .csv
            file into a DataFrame. Below we first read the file Grocery.csv into the DataFrame groceryDF. Next we set the
            Product column as the index of the DataFrame groceryDF:

             >>> import pandas as pd
             >>> groceryDF = pd.read_csv('Grocery.csv')
             >>> groceryDF.set_index('Product')
            output:
                      Product   Category  Price  Quantity
                        Bread       Food     20         2

                                                                             Data Handling using Pandas DataFrame  43
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