#!/usr/bin/env python
# coding: utf-8

# In[3]:


import psycopg2
import pandas as pd
import sqlalchemy as sa
import time
import seaborn as sns
import re


# In[36]:


get_ipython().system(' pip install pandasql')


# In[2]:


get_ipython().system(' pip install psycopg2')


# In[4]:


parameters = { 
               'username': 'postgres', 
               'password': 'root',
               'server':   'localhost',
               'database': 'ajay'
             }


# In[6]:


connection= 'postgresql://{username}:{password}@{server}:5432/{database}'.format(**parameters)


# In[17]:


print (connection)




# In[18]:


engine = sa.create_engine(connection, encoding="utf-8")




# In[19]:


insp = sa.inspect(engine)


# In[10]:


print(insp)


# In[11]:


db_list = insp.get_schema_names()
print(db_list)


# In[12]:


engine.table_names()


# In[13]:


data3= pd.read_sql_query('select * from "sales" limit 10',con=engine)


# In[14]:


data3.info()


# In[14]:


data3


# In[29]:


data5= pd.read_sql_query('select * from "sales" limit 20',con=engine)


# In[30]:


data5


# In[23]:


import pandasql as pdsql


# In[32]:


str1="select *  from data5 limit 5;"


# In[33]:


df11=pdsql.sqldf(str1)


# In[34]:


df11


# In[35]:


type(data5)


# In[43]:


data5= pd.read_sql_query('select * from "sales" limit 250',con=engine)


# In[47]:


data5.head()


# In[44]:


str2="select avg(sales)  from data5 ;"


# In[45]:


df111=pdsql.sqldf(str2)


# In[46]:


df111


# In[ ]: