Lecture: Python for Econometrics - Details

Lecture: Python for Econometrics - Details

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General information

Course name Lecture: Python for Econometrics
Subtitle
Course number 801400
Semester WiSe 2017/18
Current number of participants 24
expected number of participants 60
Home institute Ökonometrie
Courses type Lecture in category Teaching
First date Tuesday, 03.04.2018 09:00 - 12:00, Room: (Raum ZHG008: ZHG008, Gebaeude ZHG: Pl. d. Göttinger Sieben 5 (ZHG))
Type/Form
Pre-requisites Scientific Programming, Statistical Programming with R or equivalent
Performance record Written examination (90 minutes)
ECTS points 6

Rooms and times

(Raum ZHG008: ZHG008, Gebaeude ZHG: Pl. d. Göttinger Sieben 5 (ZHG))
Tuesday, 03.04.2018 09:00 - 12:00
Tuesday, 03.04.2018 13:00 - 16:00
Wednesday, 04.04.2018 09:00 - 12:00
Wednesday, 04.04.2018 13:00 - 16:00
Thursday, 05.04.2018 - Saturday, 07.04.2018 09:00 - 12:00
(Raum ZHG104, Gebaeude ZHG: Pl. d. Göttinger Sieben 5 (ZHG))
Thursday, 05.04.2018 - Saturday, 07.04.2018 13:00 - 16:00
(Raum E-Prüfungsraum MZG 1.116: E-Prüfungsraum MZG 1.116, Gebaeude MZG/Blauer Turm: Pl. d. Göttinger Sieben 5 (MZG/Blauer Turm))
Friday, 25.05.2018 12:00 - 14:00

Fields of study

Comment/Description

Contents:

In recent years, Python has established itself alongside R at the forefront of numerical programming languages. Very similar to the programming with MATLAB, mathematical-statistical representations from technical literature, such as econometric textbooks, can be implemented compactly and easily in the programming language Python and its scientific extensions. Following a concise introduction to the general-purpose language framework, the students learn how to design, implement and exchange their own data analysis projects in an object-oriented way:

1. Introduction to Python and object orientation.
2. Numerical programming - compared to MATLAB and R.
3. Data formats, handling, exports and imports - file and web.
4. Visual illustrations and presentation of scientific results.
5. Statistical analysis with further applications in economics.

The participants get familiar with Python"s way of thinking and learn how to solve (scientific) programming problems with a state-of-the-art tool.