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Basics for the use of Python in Official Statistics - 2nd edition 2024

Basics for the use of Python in Official Statistics 
Course LeaderChristian Kauth
Target Group

Official statisticians (including managers) involved in Big Data and Data Science activities having no specific knowledge on this subject;

Official statisticians (including managers) who, without being directly involved in Big Data and Data Science activities, need basic knowledge on the use of the Python language

Entry Qualifications
  • Sound command of English. Participants should be able to make short interventions and to actively participate in discussions
Objective(s)

The main objectives of the course are:

  • Introducing the participants to the Python language and ecosystem
  • Make the participants able to read and write basic Python programs for common data processing tasks (data analysis, exploration and visualization)
Contents
  • Presentations and lectures

Introduction to Python, Preparatory concepts, Documentation, Numbers and variables, Strings and sequences, Lists, tuples, sets, dictionaries, Booleans and conditional statements, Iteration and flow control, Comprehensions, Functions, Errors and exceptions, Modules, Working with files, Classes, Jupyter notebook, Package Numpy, Package Pandas, Package Scipy, Data visualizazion with matplotlib, Introduction to Scikit-learn

  • Exercises and evaluation test
Expected Outcome

The participants should have a good understanding of Python language basics and its ecosystem in order to proficiently use it for Official Statistics purposes.

Familiarity with the syntax of Python

Knowledge about the individual aspects of a data processing pipeline: reading a file, processing data, modelling, aggregation, visualization and saving results.

Experience with creation, manipulation and conversion of common data structures

Experience with writing functions and using (pre-existent) functions

Basic knowledge of important packages like Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn, Geopandas

Training Methods

The course consists of alternately:

  • Interactive presentations to introduce topics
  • Exercises (learning by doing)

For the practical hands-on parts of the course Jupyter notebook will be used and there will be a discussion regarding possible solutions to the exercises that will be assigned to participants. The participants will be stimulated to write Python code from scratch under the tutors supervision.

Required ReadingNone
Suggested Reading
Required PreparationRegister for free to the Google Colaboratory

https://colab.research.google.com/ (with personal login)
Trainer(s)/

Lecturer(s)
Christian Kauth (independent expert)

 

2nd edition

Practical Information    
WhenDurationWhereOrganiserApplication  via National Contact Point
18–22.11.20245 daysCologne, GermanyICON-INSTITUT Public Sector GmbHDeadline: 23.09.2024