Question

Use the DataFrame created in Question 9 above to do the following:

1. Display the row labels of Sales.
2. Display the column labels of Sales.
3. Display the data types of each column of Sales.
4. Display the dimensions, shape, size and values of Sales.
5. Display the last two rows of Sales.
6. Display the first two columns of Sales.
7. Create a dictionary using the following data. Use this dictionary to create a DataFrame Sales2.
   

   	2018
   Madhu	160000
   Kusum	110000
   Kinshuk	500000
   Ankit	340000
   Shruti	900000

8. Check if Sales2 is empty or it contains data.

Answer 1

import pandas as pd
Sales = pd.DataFrame
(
    {
        2014: [100.5, 150.8, 200.9, 30000, 40000],
        2015: [12000, 18000, 22000, 30000, 45000],
        2016: [20000, 50000, 70000, 100000, 125000],
        2017: [50000, 60000, 70000, 80000, 90000]
    },
    index=['Madhu', 'Kusum', 'Kinshuk', 'Ankit', 'Shruti']
)
print(Sales.index)
print(Sales.columns)
print(Sales.dtypes)
print(Sales.ndim)
print(Sales.shape)
print(Sales.size)
print(Sales.values)
print(Sales.tail(2))
print(Sales.iloc[:, :2])
data = {
    2018: [160000, 110000, 500000, 340000, 900000]
}
Sales2 = pd.DataFrame(data, index=['Madhu', 'Kusum', 'Kinshuk', 'Ankit', 'Shruti'])
print(Sales2)
print(Sales2.empty)