Python and SQL: intro / SQL platforms

obowiązkowe

The course consists of two parts: introduction to SQL (Part1) and introduction to Python (Part2).

The first part of the course provides participants with a broad introduction to SQL in the following topics :data administration (to create tables, indexes) data manipulation (to add, modify, delete and retrieve data),query construction to extract useful information.

In the second part , the material covers the use of

data structures, data manipulation and visualization in Python. The course ends with presentation of methods for joining SQL queries and Python program.

1. Relational model for database management.

2. SQL: Table manipulation and basic queries: create/drop table, select, where, insert, update

3. SQL: complex queries, joins, precuders

4. SQL: indexing, triggers

5. Python: preparation of the envrironment (Ipython Notebook/PyCharm, data structures, debugging.

6. Python: Flow control: if, for, while, iterators, error handling. Working with text files.

7. Python: Functions and classes.

8. Python: Linear algebra with NumPy

9. Python: Data handling and wrangling with Pandas.

10. Python: Visualisation with Seaborn and matpotlib.

11. Python in the web: using APIs, JSON, XML, we requests, very basic web applications.

12. Python: working with databases.

13. Presentations of projects.

1. Lutz, M. (2013) ,”Learning Python”, 5th Edition, O’Reilly

2. McKinney, W. (2012),”Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython”, O’Reilly

3. Beaulieu, A. (2009), „Learning SQL: Master SQL Fundamentals”,O’Reilly

Knowledge:

After finishing the course student knows the fundamentals of Python programming. Student knows how to use Python and its packages to prepare and analyze data to solve basic economic problems.

Skills

Student is able to prepare Python programming environment and install required packages.

Student is able to read/write, transform and aggregate data which is used in economic analysis. Student is able to prepare complex visualization to illustrate socio-economic phenomena.

Social Competence

Participant understands that the expert use of Python requires continuous practice and improvement of his own skills. This course gives him the skills to seek knowledge ,and update it to constantly changing Python libraries

Student understands that programming in Python gives a number of universal competencies, which can be applied in many areas of economics as well as other fields of knowledge.

K_U02

Final project (60%)

Written test (40%)