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19. Assuming the given table: Product. Write the python code for the following:
Item Company Rupees USD
TV LG 12000 700
TV VIDEOCON 10000 650
TV LG 15000 800
AC SONY 14000 750
a. To create the data frame for the above table.
b. To add the new rows in the data frame.
c. To display the maximum price of LG TV.
d. To display the Sum of all products.
e. To display the median of the USD of Sony products.
f. To sort the data according to the Rupees and transfer the data to MySQL.
Ans. a. To create the data frame for the above table.
import pandas as pd
myDict = {'Item':['TV','TV','TV','AC'],'Company':['LG','VIDEOCON','LG','SONY'],
'Rupees':[12000,10000,15000,14000],'USD':[700,600,800,750]}
df = pd.DataFrame(myDict)
print(df)
b. To add the new rows in the data frame.
newRows = {'Item': ['Fridge', 'Washing Machine'],
'Company': ['Whirlpool', 'Samsung'],
'Rupees': [18000, 20000],
'USD': [1000, 1200]}
df = df.append(pd.DataFrame(newRows), ignore_index=True)
print("DataFrame after adding new rows:")
print(df)
print("\n")
c. To display the maximum price of LG TV.
maxPriceLgTv = df[(df['item'] == 'TV') & (df['company'] == 'LG')]['rupees'].max()
print("Maximum price of LG TV:", maxPriceLgTv)
print("\n")
d. To display the Sum of all products.
totalSum = df['rupees'].sum()
print("Sum of all products:", totalSum)
print("\n")
e. To display the median of the USD of Sony products.
medianUsdSony = df[df['company'] == 'SONY']['usd'].median()
print("Median of USD for Sony products:", medianUsdSony)
print("\n")
f. To sort the data according to the Rupees and transfer the data to MySQL.
The following code sorts the DataFrame by the 'Rupees' column, establishes a connection to a MySQL database, and
then transfers the sorted DataFrame to a table named 'Product_table' within that database.
import pymysql
print(df.sort_values(by=['Rupees']))
Data Handling using Pandas DataFrame 87

