In [1]:
import psycopg2
import pandas as pd
import sqlalchemy as sa
import time
import seaborn as sns
import re
In [2]:
!pip install psycopg2
In [3]:
parameters = {
'username': 'postgres',
'password': 'root',
'server': 'localhost',
'database': 'datascience'
}
In [4]:
connection= 'postgresql://{username}:{password}@{server}:5432/{database}'.format(**parameters)
In [5]:
print (connection)
In [6]:
engine = sa.create_engine(connection, encoding="utf-8")
In [7]:
insp = sa.inspect(engine)
db_list = insp.get_schema_names()
print(db_list)
In [8]:
print(insp)
In [9]:
engine.table_names()
Out[9]:
In [11]:
data3= pd.read_sql_query('select * from "sales77" limit 10',con=engine)
In [12]:
print(data3)
DECISION STATS 