# import pandas library
import numpy as np
import pandas as pd
# create pandas DataFrame
df = pd.DataFrame({'Antivirus': ['Windows Defender', 'AVG Antivirus', 'Mcafee Antivirus', 'Kaspersky Security', 'Norton Antivirus'],
'quantity': [10, 4, 8, 3, 5],
'price': [23.55, np.nan, 32.78, 33.0, np.nan]
})
print("Before conversion
",df)
print("Data type of Price column is",df['price'].dtype)
# replace the NaN values for specific column
df['price'] = df['price'].replace(np.nan, 0)
#attempt to convert 'price' column from float to integer
df['price'] = df['price'].astype(int)
print("After conversion
",df)