# Data Preparation 1

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2_data_preparation_1
In [1]:
###################################################
#  Filename : 2_data_preparation_1                #
#  Purpose : To demonstrate how to construct      #
#   a coding dictionary for a discrete variable.  #
#   We use likelihood encoding.                   #
#  Author : Niel S.                               #
#  (c) The English Tea Company LLC                #
###################################################
import sys
sys.path.append('C:\\Users\\singa72\\Desktop\\Euler\\')

import Euler as Eu
from matplotlib import pyplot as plt

data_work   = data_folder+'data_work.db'

#M A I N   F U N C T I O N
def main():
#Make a coding dictionary for age;
conn = Eu.connection(data_work)

#Analyse following example
sql = '''
SELECT
marital,
sum( CASE WHEN Y = 'yes' THEN 1 ELSE 0 END) n_ppl_pass,
count(*) n_ppl_all
from bank
group by marital
'''

Eu.run(sql,conn=conn)

#Analyse this extension

sql = '''
SELECT
marital,
CASE WHEN n_ppl_all IS 0 THEN 0
ELSE round(n_ppl_pass/n_ppl_all,4) END code
FROM
(
SELECT
marital,
sum( CASE WHEN Y = 'yes' THEN 1. ELSE 0 END) n_ppl_pass,
count(*) n_ppl_all
from bank
group by marital
) as T1
'''

Eu.run(sql,conn=conn)

#Uncomment follwing to create a
# persistent coding dictionary
"""
sql = '''
DROP TABLE if exists marital_coding;
CREATE TABLE marital_coding AS
SELECT
marital,
CASE WHEN n_ppl_all IS 0 THEN 0
ELSE round(n_ppl_pass/n_ppl_all,4) END code
FROM
(
SELECT
marital,
sum( CASE WHEN Y = 'yes' THEN 1. ELSE 0 END) n_ppl_pass,
count(*) n_ppl_all
from bank
group by marital
) as T1
'''

Eu.execute(sql,conn=conn)

Eu.run('select * from marital_coding',conn)

"""

def probability_encoding_marital(conn):
'''
Exercise: Fix this function and call from main.
'''
try:
sql = '''
DROP TABLE if exists marital_coding;
CREATE TABLE marital_coding AS

'''

Eu.execute(sql,conn=conn)

except Exception as err:
Eu.print_error(err)

if __name__ == '__main__':
main()

************************************************
*                    EULER                     *
*    A SQLITE POWERED DATA SCIENCE TOOLKIT     *
*          SINGH.AP79@GMAIL.NOSPAM.COM         *
************************************************

============================
marital,n_ppl_pass,n_ppl_all
============================
divorced,476,4612
married,2532,24928
single,1620,11568
unknown,12,80
============================

============
marital,code
============
divorced,0.1032
married,0.1016
single,0.14
unknown,0.15
============



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