python

 import datetime

import pandas as pd
import cx_Oracle
con = cx_Oracle.connect('SYSTEM/oracle123@localhost:1521/xe')
c = con.cursor()
sql = "select * from covid_data"
res = c.execute(sql)
t = pd.read_sql(sql,con)
t.to_csv(r'C:\Users\abc\covid.csv')

#t.to_csv(r'C:\Users\abc\covid.csv', mode='w')

Creating SQL Hierarchical Queriy

 

PIVOT function to transform the data from rows to columns SQL

 Using the PIVOT function to transform the data from rows to columns

   -------------------------------
   | Id | Value  | ColumnName    |
   -------------------------------
   | 1  | John   | FirstName     |
   | 2  | 2.4    | Amount        |
   | 3  | ZH1E4A | PostalCode    |
   | 4  | Fork   | LastName      |
   | 5  | 857685 | AccountNumber |
   -------------------------------

This is my result:

---------------------------------------------------------------------
| FirstName  |Amount|   PostalCode   |   LastName  |  AccountNumber |
---------------------------------------------------------------------
| John       | 2.4  |   ZH1E4A       |   Fork      |  857685        |
---------------------------------------------------------------------

query :-

select Firstname, Amount, PostalCode, LastName, AccountNumber
from
(
  select value, columnname
  from yourtable
) d
pivot
(
  max(value)
  for columnname in (Firstname, Amount, PostalCode, LastName, AccountNumber)
) piv;

CASE expression:

select
  max(case when columnname = 'FirstName' then value end) Firstname,
  max(case when columnname = 'Amount' then value end) Amount,
  max(case when columnname = 'PostalCode' then value end) PostalCode,
  max(case when columnname = 'LastName' then value end) LastName,
  max(case when columnname = 'AccountNumber' then value end) AccountNumber
from yourtable