---
# System prepended metadata

title: Vaishali Gupta

---

# 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');





```

