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Juris_CSV_to_SQL.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Dec 25 15:38:37 2018
@author: AYang
Project: 2017 housing permit inventory
Task: convert jurisdictions' 2017 permit from csv file to SQL database
"""
import pandas as pd
import pyodbc
import numpy as np
import os
COUNTY = 'KITSAP'
COUNTY_CODE = '35'
def read_data(DATA_PATH, COUNTY, COUNTY_CODE, JURI):
juri_name = 't' + COUNTY_CODE + JURI + '_final.txt'
my_juri = pd.DataFrame.from_csv(os.path.join(DATA_PATH, COUNTY, juri_name), sep=',', index_col=None)
return my_juri
# add more columns to process duplicated data and other usages, from current year to previous years
def data_process(my_data, col1):
## add some columns
my_data[col1] = 0
if 'PIN_PARENT' not in my_data.columns:
my_data['PIN_PARENT'] = np.nan
if 'COUNTY' not in my_data.columns:
my_data['COUNTY'] = COUNTY
if 'LOTSIZE' not in my_data.columns:
my_data['LOTSIZE'] = np.nan
if 'ID' not in my_data.columns:
my_data['ID'] = np.nan
# reorder the csv table columns, so it could line up with the SQL table columns. It is important in the data type specification, apple to apple.
my_data = my_data[[u'ID', u'PSRCIDN', u'PERMITNO', u'SORT', u'MULTIREC', u'PIN',
u'ADDRESS', u'HOUSENO', u'PREFIX', u'STRNAME', u'STRTYPE', u'SUFFIX',
u'UNIT_BLD', u'ZIP', u'ISSUED', u'FINALED', u'STATUS', u'TYPE', u'PS',
u'UNITS', u'BLDGS', u'LANDUSE', u'CONDO', u'VALUE', u'ZONING', u'NOTES',
u'NOTES2', u'NOTES3', u'NOTES4', u'NOTES5', u'NOTES6', u'NOTES7',
u'LOTSIZE', u'JURIS', u'JURIS15', u'PLC', u'PLC15', u'PROJYEAR',
u'CNTY', u'MULTCNTY', u'PSRCID', u'PSRCIDXY', u'X_COORD', u'Y_COORD',
u'RUNTYPE', u'CHECK_DUPLICATED', u'PIN_PARENT', u'COUNTY']]
return my_data
## convert empty string as numpy nan value
'''
replace panda or numpy value none to NULL, or the SQL server won't recogonize the NULL value.
referrence: https://stackoverflow.com/questions/14162723/replacing-pandas-or-numpy-nan-with-a-none-to-use-with-mysqldb
'''
def process_null_data(my_data):
my_data.replace('', np.nan, inplace=True)
print (np.where(my_data.applymap(lambda x: x == '')))
my_data = my_data.where((pd.notnull(my_data)), None)
return my_data
## get the existing table list from the SQL database
def get_table_from_elmer():
table_names = []
for rows in cursor.tables():
if rows.table_type == "TABLE":
table_names.append(rows.table_name)
return table_names
## if the table name already duplicated in the SQL database (Sandbox here), then delete the previous table! Please be very careful of this step!!!!
def check_duplicated_table(table_names, my_tablename):
table_exists = my_tablename in table_names
if table_exists == True:
print 'There is currently a table named ' + my_tablename + ', removing the older table'
sql_statement = 'drop table ' + my_tablename
cursor.execute(sql_statement)
sql_conn.commit()
## get column list from original csv table, to help construct the SQL data table
def get_col_list(my_data):
str_c = ''
for c in final_data.columns.tolist()[0:]:
str_c = str_c + '[' + c + '],'
str_c = str_c[:-1]
return str_c
## create data table structure in SQL and specific data types
def create_data_table_in_SQL(sql_statement):
cursor.execute(sql_statement)
sql_conn.commit()
# insert data into table
def insert_data_into_SQL(my_data, str_c, my_tablename):
for index,row in my_data.iterrows():
print (index)
#print (row)
sql_state = 'INSERT INTO ' + my_tablename + '(' + str_c + ')' + 'values (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)'
cursor.execute(sql_state, row['ID'],row['PSRCIDN'],row['PERMITNO'],row['SORT'],row['MULTIREC'],
row['PIN'],row['ADDRESS'],row['HOUSENO'],row['PREFIX'],row['STRNAME'],
row['STRTYPE'],row['SUFFIX'],row['UNIT_BLD'],row['ZIP'],row['ISSUED'],
row['FINALED'],row['STATUS'],row['TYPE'],row['PS'],row['UNITS'],
row['BLDGS'],row['LANDUSE'],row['CONDO'],row['VALUE'],row['ZONING'],
row['NOTES'],row['NOTES2'],row['NOTES3'],row['NOTES4'],row['NOTES5'],
row['NOTES6'],row['NOTES7'],row['LOTSIZE'],
row['JURIS'],row['JURIS15'],row['PLC'],row['PLC15'],row['PROJYEAR'],
row['CNTY'],row['MULTCNTY'],row['PSRCID'],row['PSRCIDXY'],row['X_COORD'],
row['Y_COORD'],row['RUNTYPE'],row['CHECK_DUPLICATED'], row['PIN_PARENT'],row['COUNTY'])
sql_conn.commit()
################################ START THE PROCESS #####################################
## 1. prepare data
## get the data and prepare the data for SQL read
if COUNTY is 'KING':
JURIS_list = ['ALGONA2', 'BELLEVUE', 'BLACKDIAMOND2', 'BURIEN', 'CARNATION', 'CLYDEHILL', 'COVINGTON',
'DESMOINES', 'ENUMCLAW', 'FEDERALWAY', 'ISSAQUAH2', 'KENMORE','KENT', 'KIRKLAND',
'LAKEFORESTPARK', 'MAPLEVALLEY', 'MEDINA', 'MERCERISLAND', 'NEWCASTLE', 'NORMANDYPARK',
'SAMMAMISH', 'SEATAC', 'SEATTLE2', 'SHORELINE', 'SNOQUALMIE', 'UNINCORPORATED',
'WOODINVILLE2', 'YARROWPOINT']
if COUNTY is 'KITSAP':
JURIS_list = ['BREMERTON', 'PORTORCHARD', 'POULSBO', 'UNINCORPORATED']
if COUNTY is 'PIERCE':
JURIS_list = ['BUCKLEY', 'CARBONADO', 'DUPONT', 'EATONVILLE', 'EDGEWOOD',
'FIFE', 'FIRCREST', 'GIGHARBOR', 'ORTING', 'PUYALLUP', 'STEILACOOM',
'SUMNER', 'TACOMA', 'UNINCORPORATED', 'UNIVERSITYPLACE', 'WILKESON']
if COUNTY is 'SNOHOMISH':
JURIS_list = ['ARLINGTON', 'BOTHELL1', 'BOTHELL2', 'BRIER', 'DARRINGTON', 'EDMONDs',
'EVERETT', 'GOLDBAR', 'GRANITEFALLS', 'LAKESTEVENS', 'LYNNWOOD', 'MARYSVILLE',
'MILLCREEK', 'MONROE', 'MOUNTLAKETERRACE', 'MUKILTEO', 'SNOHOMISH',
'STANWOOD', 'UNINCORPORATED', 'WOODWAY']
'''
to get the list of files in a directory:
from os import listdir
path = r'J:\Projects\Permits\17Permit\database\working\SNOHOMISH'
os.listdir(path)
'''
## 2. SQL Connection to our internal SQL database Elmer
sql_conn = pyodbc.connect('DRIVER={SQL Server}; SERVER=sql2016\DSADEV;DATABASE=Sandbox;trusted_connection=true')
cursor = sql_conn.cursor()
#JURI = 'POULSBO'
for JURI in JURIS_list:
print (JURI)
DATA_PATH = r'J:\Projects\Permits\17Permit\database\working'
if JURI == 'UNINCORPORATED':
my_tablename = JURI + COUNTY + '17'
else:
my_tablename = JURI + '17'
## set up the SQL data table structure (the data types would change from table to table)
sql_statement1 = 'create table ' + my_tablename
sql_statement2 = '( ' + \
'ID INT NULL, ' + \
'PSRCIDN varchar(255) NULL, ' + \
'PERMITNO varchar(255) NULL, ' + \
'SORT varchar(255) NULL, ' + \
'MULTIREC varchar(255) NULL, ' + \
'PIN varchar(255) NULL, ' + \
'ADDRESS varchar(255) NULL, ' + \
'HOUSENO varchar(255) NULL, ' + \
'PREFIX varchar(255) NULL, ' + \
'STRNAME varchar(255) NULL, ' + \
'STRTYPE varchar(255) NULL, ' + \
'SUFFIX varchar(255) NULL, ' + \
'UNIT_BLD varchar(255) NULL, ' + \
'ZIP varchar(255) NULL, ' + \
'ISSUED date NULL, ' + \
'FINALED date NULL, ' + \
'STATUS varchar(255) NULL, ' + \
'TYPE INT NULL, ' + \
'PS INT NULL, ' + \
'UNITS varchar(255) NULL, ' + \
'BLDGS varchar(255) NULL, ' + \
'LANDUSE varchar(255) NULL, ' + \
'CONDO varchar(255) NULL, ' + \
'VALUE varchar(255) NULL, ' + \
'ZONING varchar(255) NULL, ' + \
'NOTES nvarchar(500) NULL, ' + \
'NOTES2 varchar(255) NULL, ' + \
'NOTES3 varchar(255) NULL, ' + \
'NOTES4 varchar(255) NULL, ' + \
'NOTES5 varchar(255) NULL, ' + \
'NOTES6 varchar(255) NULL, ' + \
'NOTES7 varchar(255) NULL, ' + \
'LOTSIZE varchar(255) NULL, ' + \
'JURIS varchar(255) NULL, ' + \
'JURIS15 INT NULL, ' + \
'PLC INT NULL, ' + \
'PLC15 varchar(255) NULL, ' + \
'PROJYEAR INT NULL, ' + \
'CNTY INT NULL, ' + \
'MULTCNTY varchar(255) NULL, ' + \
'PSRCID varchar(500) NULL, ' + \
'PSRCIDXY varchar(500) NULL, ' + \
'X_COORD float NULL, ' + \
'Y_COORD float NULL, ' + \
'RUNTYPE INT NULL, '+\
'CHECK_DUPLICATED INT NULL, ' +\
'PIN_PARENT varchar(255) NULL, ' + \
'COUNTY varchar(255) NULL)'
final_data = read_data(DATA_PATH, COUNTY, COUNTY_CODE, JURI)
final_data = data_process(final_data, 'CHECK_DUPLICATED')
final_data = process_null_data(final_data)
table_names = get_table_from_elmer()
print table_names
check_duplicated_table(table_names, my_tablename)
str_c = get_col_list(final_data)
## 3. exactive the SQL process
sql_statement = sql_statement1 + sql_statement2
create_data_table_in_SQL(sql_statement)
insert_data_into_SQL(final_data, str_c, my_tablename)
print (JURI)
print ('-----------------finished------------------')
print ('Closing the central database')
sql_conn.close()