create sqlite database python
import sqlite3
import pandas as pd
from pandas import DataFrame
conn = sqlite3.connect('TestDB.db')
c = conn.cursor()
read_clients = pd.read_csv (r'C:UsersRonDesktopClientClient_14-JAN-2019.csv')
read_clients.to_sql('CLIENTS', conn, if_exists='append', index = False) # Insert the values from the csv file into the table 'CLIENTS'
read_country = pd.read_csv (r'C:UsersRonDesktopClientCountry_14-JAN-2019.csv')
read_country.to_sql('COUNTRY', conn, if_exists='replace', index = False) # Replace the values from the csv file into the table 'COUNTRY'
# When reading the csv:
# - Place 'r' before the path string to read any special characters, such as ''
# - Don't forget to put the file name at the end of the path + '.csv'
# - Before running the code, make sure that the column names in the CSV files match with the column names in the tables created and in the query below
# - If needed make sure that all the columns are in a TEXT format
c.execute('''
INSERT INTO DAILY_STATUS (Client_Name,Country_Name,Date)
SELECT DISTINCT clt.Client_Name, ctr.Country_Name, clt.Date
FROM CLIENTS clt
LEFT JOIN COUNTRY ctr ON clt.Country_ID = ctr.Country_ID
''')
c.execute('''
SELECT DISTINCT *
FROM DAILY_STATUS
WHERE Date = (SELECT max(Date) FROM DAILY_STATUS)
''')
#print(c.fetchall())
df = DataFrame(c.fetchall(), columns=['Client_Name','Country_Name','Date'])
print (df) # To display the results after an insert query, you'll need to add this type of syntax above: 'c.execute(''' SELECT * from latest table ''')
df.to_sql('DAILY_STATUS', conn, if_exists='append', index = False) # Insert the values from the INSERT QUERY into the table 'DAILY_STATUS'
# export_csv = df.to_csv (r'C:UsersRonDesktopClientexport_list.csv', index = None, header=True) # Uncomment this syntax if you wish to export the results to CSV. Make sure to adjust the path name
# Don't forget to add '.csv' at the end of the path (as well as r at the beg to address special characters)
