# Vaishali Gupta | ~2 yrs exp - Good with data transformation - ETL pipeline - Good for next round # Question 1: Data Transformation ```python! const Data = [{ 5: { 10: ['B', 'D', 'F'] }, 6: { 9: ['A'], 11: ['C'], 12: ['E'] }, 7: { 12: ['G'] } }] import pandas as pd import json data_1=df.json_load('data') data_2 =pd.json_normalize('data_1', {5,{10,meta{'B','D','F'}}},{{6,{9,meta {'A'}}},{6,{11,meta{'C'}}},{6,{12,meta{'E'}}},{7,{12,meta {'G'}}}) data_3 = df.DataFrame('data_2',columns {'Classes','Ages','Names'},inplace=True) print(data_3) ------------------ for item in data : for subitem in item[] select account_id, name from contract_account_id where salary > 10000 and (id) in (select id from contract_customer where client_id='2004' and clent_cd='CDS'); ```