Poslední úprava: Mgr. Bc. Vít Macháček (12.10.2021)
The aim of the course is to provide hands-on experience to programming in Python with the special emphasis on data-manipulation and web-scraping.
Online meeting is available at: https://meet.google.com/zda-kefi-bsq?
Students will get the basics of Pandas, Numpy or Matplotlib and also collecting web data with requests and BeatifiulSoup. The students will also be guided through the modern social-coding and open-source technologies such as GitHub, Jupyter and Open Data.
The students will gain their experience using the data from the IES website and subject evaluation protocols.
The course would make use of the DataCamp online sources ( https://www.datacamp.com ) to provide the students with reliable and yet simple resources for learning Python programming.
Poslední úprava: Mgr. Jan Šíla, M.Sc. (10.02.2022)
The course site for the Data Processing in Python from IES. See information on SIS. The course is taught by Martin Hronec, Vítek Macháček and Jan Šíla.
Stable link for online attendance: Join Zoom Meeting https://cesnet.zoom.us/j/92851968819?pwd=L296R2N1T1RNR2VPdVMxQjdQR1Iydz09
Meeting ID: 928 5196 8819 Passcode: pythonFTW
The aim of the course is to provide hands-on experience to programming in Python with a special emphasis on data manipulation and web-scraping.
For more detailed, lecture-by-lecture content, please see the course's GitHub repository ( https://github.com/vitekzkytek/PythonDataIES/blob/master/README.md ).
Students will get the basics of Pandas, Numpy or Matplotlib and also collect web data with requests and BeatifiulSoup. The students will also be guided through the modern social-coding and open-source technologies such as Git (+GitHub), Jupyter and Open Data.
The students will gain their experience using the data from the IES website and subject evaluation protocols.
The course makes use of the DataCamp online sources ( https://www.datacamp.com ) to provide the students with reliable and yet simple resources for learning Python programming.
Cíl předmětu -
Poslední úprava: SCHNELLEROVA (24.10.2019)
Please switch to the english version.
Poslední úprava: Mgr. Martin Hronec (06.02.2020)
After passing the course, the students will be able to execute a software-based, data-oriented project in Python, specifically download the data from APIs or directly from the web, pre-process it, analyze it and visualize it. Further, they will be able to do it in a repeatable, standard software-development quality manner using version control.
Literatura -
Poslední úprava: Mgr. Michaela Čuprová (02.02.2020)
Book
Wes McKinney: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, O'Reilly, 2012
Grading scale (according to Dean's Provision 17/2018):
A: above 90 (not inclusive)
B: between 80 (not inclusive) and 90 (inclusive)
C: between 70 (not inclusive) and 80 (inclusive)
D: between 60 (not inclusive) and 70 (inclusive)
E: between 50 (not inclusive) and 60 (inclusive)
F: below 50 (inclusive)
Sylabus -
Poslední úprava: PhDr. Petr Bednařík, Ph.D. (15.02.2020)
Previous experience with general coding is assumed - The course is designed for students that have at least some basic coding experience. It does not need to be very advanced, but they should be aware of concepts such as for loop, if and else, variable or function.
No knowledge of Python is required for entering the course.
Poslední úprava: Mgr. Jan Šíla, M.Sc. (10.02.2022)
Previous experience with general coding is assumed - The course is designed for students that have at least some basic coding experience. It does not need to be very advanced, but they should be aware of concepts such as for loop, if and else, variable or function.
No knowledge of Python is required for entering the course.
Date
Topic
who
Project
HW
15/2
Intro, Jupyter, Git (+ GitHub)
Martin
21/2
Seminar (Git)
Martin
HW 1
22/2
Strings, Floats, Lists, Dictionaries, Functions
Vitek
HW 0
1/3
Numpy, Pandas, Matplotlib
Jan
HW 2
7/3
Seminar
Jan
8/3
Object-Oriented Programming
Martin
HW 3
15/3
HTML, XML, JSON, requests, APIs, BeautifulSoup
Jan
21/3
IES Web Scraper
Vitek
HW 4
22/3
Seminar
Vitek
29/3
Advanced Pandas
Vitek
HW 5
4/4
Introduction to Databases
Jan
Project Topic Proposal
HW 6
5/4
Seminar - MIDTERM
full house
11/4
Packaging and Documentation
Martin
12/4
Testing (and decorators)
Martin
19/4
Seminar
Martin
Project Topic Approval
26/4
Guest lecture
TBD
2/5
Project Work 2 (Seminar)
full house
Work-in-progress
3/5
Project Work 2
full house
Work-in-progress
X/X
Project Deadline
full house
Vstupní požadavky -
Poslední úprava: SCHNELLEROVA (24.10.2019)
Please switch to the english version.
Poslední úprava: Mgr. Martin Hronec (06.02.2020)
Previous experience with general coding is assumed - The course is designed for students that have at least some basic coding experience. It does not need to be very advanced, but they should be aware of concepts such as for loop, if and else, variable or function.
No knowledge of Python is required for entering the course.
Požadavky k zápisu -
Poslední úprava: SCHNELLEROVA (24.10.2019)
Please switch to the english version.
Poslední úprava: Mgr. Martin Hronec (06.02.2020)
The course is primarily for master and advanced bachelor students.
For bachelors, Econometrics II (JEB110) is a prerequisite.
