# 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');
```