PostgreSQL Databases: Connect To R and Python

PostgreSQL Databases: Connect To R and PythonMichael Grogan (MGCodesandStats)BlockedUnblockFollowFollowingFeb 22PostgreSQL is a commonly used database language for creating and managing large amounts of data effectively.

Here, you will see how to:create a PostgreSQL database using the Linux terminalconnect the PostgreSQL database to R using the “RpostgreSQL” library, and to Python using the “psycopg2” libraryCreating our PostgreSQL databaseIn this example, we are going to create a simple database containing a table of dates, cities, and average temperature in degrees (Celsius).

We will name our database weather, and our table cities.

Once we open a Linux terminal, we enter the following:sudo -u postgres createdb weathersudo -u postgres psql weatherThis creates our weather database.

We then enter password to set a password:passwordOnce prompted, we will enter a password rainbow, or whatever password you preferEnter new password: rainbowEnter it again: rainbowWe then enter psql to initiate PostgreSQL and conninfo to test the connection:weather=# psqlweather-# conninfoYou are connected to database "weather" as user "postgres" via socket in "/var/run/postgresql" at port "5432".

Create Table for DatabaseOnce we have verified our connection, we can now create the table.

As mentioned, we will name our table cities, and include the fields date, city_name, and averagetemp_celsius.

We will define each variable as DATE, VARCHAR(50), and DECIMAL(7,2) respectively.

CREATE TABLE cities ( date DATE, city_name VARCHAR(50), averagetemp_celsius DECIMAL(7,2));Once that’s done, we can then insert the appropriate values into our table:INSERT INTO cities VALUES('02/08/2017', 'New York', 25),('02/08/2017','Los Angeles',28),('03/08/2017','London',18),('03/08/2017','Paris',22),('03/08/2017','Los Angeles',28),('04/08/2017','Berlin',18),('04/08/2017','Tokyo',25),('05/08/2017','Zurich',24),('05/08/2017','Shanghai',29);Connect Python to Database using psycopg2We import our psycopg2 library, and enter our database credentials:import psycopg2conn = psycopg2.

connect("dbname=weather user=postgres password=rainbow host=localhost")Now, let’s execute two commands.

Firstly, we wish to insert an extra row of data into our database from Python directly:cur = conn.

cursor()cur.

execute("INSERT INTO cities (date, city_name,averagetemp_celsius) VALUES (%s, %s, %s)",.

("05/08/2017", "Sydney", "16"))Once we have done that, we can then display our data within the Python console:cur.

execute("SELECT date, city_name, averagetemp_celsius from cities")rows = cur.

fetchall()And, we see that our data is displayed in the Python console:In order to make the changes to the database permanent, we now commit our changes to the cities database:conn.

commit()We have committed the necessary changes and can now close out our connection:cur.

close()conn.

close()Connect R to database using RpostgreSQLFirstly, we install the RpostgreSQL package:install.

packages("RPostgreSQL")require("RPostgreSQL")Then, we define the database password within R:pw <- { "rainbow"}We define our driver and set up the connection:drv <- dbDriver("PostgreSQL")con <- dbConnect(drv, dbname = "weather", host = "localhost", port = 5432, user = "postgres", password = pw)rm(pw)We verify that the “cities” table exists:dbExistsTable(con, "cities")Once verified, we read our table into R using dbReadTable:myTable <- dbReadTable(con,c("cities"))attach(myTable)And there’s our table — we’ve successfully connected our PostgreSQL database to R!.You might also find the following tutorial helpful in using PostgreSQL with Ubuntu.

dbSendQuery: Editing database directly from RNow that we’ve created our database, what if we wish to edit directly from R?.For instance, suppose that we have a new row of values that we would like to input.

Instead of having to access the PostgreSQL database directly every time, we would like to send a query from R that does this for us.

Let us suppose that we wish to insert the following three values: ‘06/08/2017’, ‘Sao Paulo’, ‘16’.

To do this, we create a variable res that uses a dbSendQuery command to send an INSERT INTO query as follows:res <- dbSendQuery(con, statement=paste("INSERT INTO cities (date, city_name, averagetemp_celsius) VALUES ('06/08/2017', 'Sao Paulo', '16')"));Once we have sent the query, we now see that upon opening the associated data frame in R, our entry for Sao Paulo has been included and our query has been committed!ConclusionIn this tutorial, you have learned how to:Create a database and table in PostgreSQLConnect a Python environment to a database using psycopg2Commit queries to the database and add additional entriesThe original post can be viewed at michaeljgrogan.

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