2017 Python Pandas: connect & import directly any database
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2017 Python Pandas: connect & import directly any database

ORACLE Database, IBM Db2, MS SQL Server, MySQL, Postgresql, SQLite
New
5.0 (2 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
17 students enrolled
Created by Code Pro
Last updated 8/2017
English
Current price: $12 Original price: $65 Discount: 82% off
4 days left at this price!
30-Day Money-Back Guarantee
Includes:
  • 2.5 hours on-demand video
  • 13 Articles
  • 5 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion

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What Will I Learn?
  • How to install major database software: Oracle Database, IBM Db2, MS SQL Server, MySQL, PostgreSQL, SQLite
  • How to install management tools for each database software: Oracle SQL Developer, IBM Data Studio, SSMS, MySQL Workbench, pgAdmin, DB Browser for SQLite
  • Where to find sample databases for each and how to import them
  • How to connect directly with Python to each database
  • How to import data directly to Pandas DataFrames
View Curriculum
Requirements
  • Basics of Python and Pandas.
Description

Don't be the guy who can only import a csv file into Pandas, learn the techniques to connect directly with Python to a variety of database sources and import data directly into Pandas DataFrames. 

At the end of this course you will be able to connect and import directly from ORACLE Database, IBM DB2, MS SQL Server, MySQL, Postgresql, and SQLite, and you will know how to deal with tricky connection parameter and where to find them.

This course is design for you to stand out from the crowd.

Who is the target audience?
  • Anyone who wants to be able to retrieve data with Python directly from any database and import it into Pandas DataFrames.
Compare to Other Python Courses
Curriculum For This Course
32 Lectures
02:23:42
+
Introduction
1 Lecture 05:30

This lecture provides the overall structure of the course as well as installation steps for Python, Pandas and Jupyter notebook (the browser based code editor you used throughout this course).

Preview 05:30
+
SQLite
4 Lectures 12:56

In this lecture I walk you through the installation of SQLite, DB Browser for SQLite and a sample database.

Preview 05:17

Learn how to import data directly from SQLite database using Python and import it into a Pandas DataFrame.

THE CODE: How to import directly from SQLite
07:23

This is a practice question.

Practice: What is missing in this code?
00:07

This provides the answer to the practice question

Practice Answer
00:08
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MS SQL SERVER
5 Lectures 25:07

In this lecture I take you through the installation of MS SQL Server and SSMS, SQL Server Management Studio.

MS SQL Server & SQL Server Management Studio (SSMS)
03:41

In this lecture you will learn where to find sample databases for MS SQL Server, where to save them, and how to bring them in SSMS.

Sample database for MS SQL Server
09:58

In this lecture you will learn how to connect directly with Python to MS SQL Server, retrieve data and import it directly into a Pandas DataFrame.

THE CODE: How to import directly from MS SQL Server
10:51

This is a practice question

Practice: What code would you write in this case?
00:21

Answer to the practice question

Practice answer
00:16
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ORACLE
4 Lectures 19:59

This lecture takes you through the installation of Oracle database and Oracle SQL Developer.

Oracle Database & Oracle SQL Developer: Installation and configuration
03:44

In this lecture you will learn how to connect directly with Python to an Oracle Database, retrieve data and import it directly into a Pandas DataFrame.

THE CODE: How to import directly from an ORACLE Database
15:45

Practice question.

Practice: Where do you find the following 2 connection parameters?
00:03

Answer to practice question.

Practice answer
00:26
+
IBM
7 Lectures 50:45

In this lecture I walk you through the installation and configuration of IBM Db2 and IBM Data Studio.

IBM Db2 and IBM Data Studio: Installation and configuration
07:38

This lecture walks you through the creation of a sample IBM database that you will use to import data directly from IBM to a Pandas DataFrame.

Create sample IBM database
03:35

In this lecture I explain briefly the difference between a catalogued and an uncatalogued IBM database as these will be addressed differently in connection with Python Pandas.

Catalogued vs Uncatalogued database
01:25

You will learn how to import data directly from an uncatalogued IBM database using Python into a Pandas DataFrame.

THE CODE: import directly from an uncatalogued IBM database
33:40

In this lecture you will learn how to connect directly with Python to a catalogued IBM database, retrieve data and import it directly into a Pandas DataFrame.

THE CODE: import directly from a catalogued IBM database
04:14

Practice question.

Practice: What privileges are needed?
00:05

Answer to practice question.

Practice answer
00:08
+
MySQL
5 Lectures 15:53

In this lecture I walk you through the installation and configuration of MySQL database Server and MySQL Workbench, the management tools for MySQL Database.

MySQL & MySQL Workbench
05:13

You will learn how to import a sample database in MySQL Workbench.

MySQL sample database
05:06

In this lecture you will learn how to connect directly with Python to MySQL Database, retrieve data and import it directly into a Pandas DataFrame.

THE CODE: How to import directly from MySQL
05:20

Practice question.

Practice: what code do you need?
00:05

Answer for practice question.

Practice Answer
00:09
+
PostgreSQL
6 Lectures 13:49

In this lecture I walk you through the installation and configuration of PostgreSQL Database Server and pgAdmin4, the management tools for PostgreSQL database.

PostgreSQL and pgAdmin
03:00

Here you will learn where to get a sample database for your PostgreSQL database Server and how to bring it in pgAdmin.

PostgreSQL sample database
06:00

In this lecture you will learn how to connect directly with Python to PostgreSQL Database, retrieve data and import it directly into a Pandas DataFrame.

THE CODE: How to import directly from PostgreSQL
04:15

Practice question

Practice: What is the code?
00:05

Answer to practice question.

Practice Answer
00:08

This lecture closes the course.

Closing lecture
00:21
About the Instructor
Code Pro
5.0 Average rating
2 Reviews
17 Students
1 Course
Experienced Pro|Python|ExxonMobil Shell BP Unilever PwC KPMG

I have 15 years’ experience providing professional services to major companies such as ExxonMobil, Shell, British Petroleum, Unilever, PriceWaterHouseCoopers, KPMG, Unilever, PwC, KPMG, Avery Dennison, DuPont, Medtronic, Imperial Tobacco, Fiat... 

I have worked on high profile projects including the bribery investigation that led the US Department of Justice to impose criminal and civil penalties for bribery on Oil companies. This involved of the use of advance data analysis to acquire evidence.

Specialised in Python, Pandas (Data Analysis), SQL, Django, Bokeh (Data Visualisation), DataShader and Kivy.

I was part of building the biggest commercial data Mart, processing some 350 million transactions per query.

I enjoy sharing knowledge, and I hope you will enjoy and benefit from my courses.