Data Processing in Python - JEM207

• Anglický název: Data Processing in Python
• Český název: Data Processing in Python
• Zajišťuje: Institut ekonomických studií (23-IES)
• Fakulta: Fakulta sociálních věd
• Platnost: od 2023
• Semestr: oba
• E-Kredity: 5
• Způsob provedení zkoušky: písemná
• Rozsah, examinace: 2/0, Zk [HT]
• Počet míst: zimní:130 / neurčen (60); letní:neurčen / neurčen (60)
• Minimální obsazenost: neomezen
• 4EU+: ne
• Virtuální mobilita / počet míst pro virtuální mobilitu: ne
• Stav předmětu: vyučován
• Jazyk výuky: angličtina
• Způsob výuky: prezenční
• Způsob výuky: prezenční
• Poznámka: předmět je možno zapsat mimo plán; povolen pro zápis po webu; při zápisu přednost, je-li ve stud. plánu; předmět lze zapsat v ZS i LS
• Garant: PhDr. František Čech, Ph.D.; Mgr. Martin Hronec
• Vyučující: PhDr. František Čech, Ph.D.; Mgr. Martin Hronec; Mgr. Bc. Vít Macháček, Ph.D.; Ing. Alena Pavlova; Mgr. Jan Šíla, M.Sc.
• Třída: Courses for incoming students

Anotace

čeština

Poslední úprava: Mgr. Jan Šíla, M.Sc. (06.02.2023)

The course is taught in person and we expect students to come to the class to attend the lectures and seminars.

The aim of the course is to provide hands-on experience in programming in Python with a special emphasis on data manipulation and processing.

Students will get the basics of Pandas, Numpy or Matplotlib and also collect web data with API requests and BeatifiulSoup. The students will also be guided through modern social-coding and open-source technologies such as GitHub, Jupyter and Open Data.

The students will gain 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 yet simple resources for learning Python programming.

Cíl předmětu

čeština

Poslední úprava: SCHNELLEROVA (24.10.2019)

Please switch to the english version.

angličtina

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

čeština

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

https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793

 

Recommended DataCamp Courses

General Python

Introduction to Python

Intermediate Python for Data Science

 

Pandas

pandas Foundations

Manipulating DataFrames with pandas

Merging DataFrames with pandas

Cleaning Data in Python

 

Web Data Formats

Importing Data in Python (Part 1)

Importing Data in Python (Part 2)

Web Scraping with Python

 

Data Visualizations

Introduction to Data Visualization

Interactive Data Visualization in Bokeh

 

SQL

Introduction to SQL for Data Science

Introduction to Databases in Python

 

Others

LearnPython

Learn Python on CodeAcademy

Pandas

Practical Introduction to Web Scraping in Python

 

Official Documentation

Python

Pandas

Numpy

requests

BeautifulSoup 

Matplotlib

 

 

angličtina

Poslední úprava: Mgr. Bc. Vít Macháček, Ph.D. (07.01.2019)

Book

Wes McKinney: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, O'Reilly, 2012

https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793

 

Recommended DataCamp Courses

General Python

Introduction to Python

Intermediate Python for Data Science

 

Pandas

pandas Foundations

Manipulating DataFrames with pandas

Merging DataFrames with pandas

Cleaning Data in Python

 

Web Data Formats

Importing Data in Python (Part 1)

Importing Data in Python (Part 2)

Web Scraping with Python

 

Data Visualizations

Introduction to Data Visualization

Interactive Data Visualization in Bokeh

 

SQL

Introduction to SQL for Data Science

Introduction to Databases in Python

 

Others

LearnPython

Learn Python on CodeAcademy

Pandas

Practical Introduction to Web Scraping in Python

 

Official Documentation

Python

Pandas

Numpy

requests

BeautifulSoup 

Matplotlib

 

 

Metody výuky

čeština

Poslední úprava: Mgr. Martin Hronec (14.02.2020)

Please switch to the english version.

angličtina

Poslední úprava: Mgr. Martin Hronec (06.02.2020)

Please see the course GitHub repository (https://github.com/vitekzkytek/PythonDataIES/blob/master/README.md).

Požadavky ke zkoušce

čeština

Poslední úprava: SCHNELLEROVA (24.10.2019)

Please switch to the english version.

angličtina

Poslední úprava: Mgr. Jan Šíla, M.Sc. (05.12.2023)

The final grade consists of four parts:

• Homework assignments (5%)
• Midterm (25%)
• Presentation of work in progress on the final project (10%) - at least 50% required from this part
• Final project (60%) - at least 50% required from this part

more info on the course GitHub( https://github.com/vitekzkytek/PythonDataIES/blob/master/README.md )

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

čeština

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.

 

Topics:

• Intro + GitHub, Jupyter, DataCamp
• Strings, Floats, Integers, Lists, Dictionaries, Functions
• Pandas, Matplotlib, Numpy
• Object-Oriented Programming
• HTML, XML, JSON
• API + Scraping
• Advanced Pandas
• SQLite
• Efficient Computing
• Project Work 1
• Project Work 2
• Bokeh + GitHub Pages

angličtina

Poslední úprava: Mgr. Martin Hronec (05.02.2024)

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

| Week | Date | L/S | Topic | Lecturer | Deadline || --- | --- | --- | --- | --- | --- |
| 1 | 19.2. | S | Seminar 0: Setup (Jupyter, VScode, Git, OS basics) | Martin + Alena |  |
| 1 | 20.2. | L | Python basics | Martin |  |
| 2 | 27.2. | L | Python basics II | Jan |  |
| 3 | 4.3. | S | Seminar 1: Basics | Alena | HW 1 |
| 3 | 5.3. | L | Numpy | Jan |  |
| 4 | 12.3. | L | Pandas I | Martin |  |
| 5 | 18.3. | S | Seminar 2: Numpy & pandas | Alena | HW 2 |
| 5 | 19.3. | L | Pandas II + Matplotlib | Martin |  |
| 6 | 26.3. | L | Data formats, APIs | Jan |  |
| 7 | 2.4. | S | Seminar 3: Data formats & APIs | Alena | HW 3 |
| 7 | 8.4. | - | MIDTERM | Alena, Jan & Martin |  |
| 8 | 9.4 | L | Algorithmic problem solving  | Jan |  |
| 9 | 15.4. | S | MIDTERM solution | Alena |  |
| 9 | 16.4. | L | Data science | Martin |  |
| 10 | 23.4. | L | How to code (avoiding spaghetti code) | Martin | Project proposal |
| 11 | 29.4. | S | Seminar 5: Data science case-study | Alena |  |
| 11 | 30.4. | L | Databases | Jan | Topic approved |
| 12 | 7.5. | L | Guest Lecture + Beer after lecture @ https://pivo-klub.cz/ | TBD |  |
| 13 | 12.-16.5. | - | WiP: Project consultations | Alena, Jan & Martin |  |
| 14 | 20.-23.5. | - | WiP: Project consultations | Alena, Jan & Martin |  |

Vstupní požadavky

čeština

Poslední úprava: SCHNELLEROVA (24.10.2019)

Please switch to the english version.

angličtina

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.

angličtina

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

čeština

Poslední úprava: SCHNELLEROVA (24.10.2019)

Please switch to the english version.

angličtina

Poslední úprava: Mgr. Martin Hronec (04.10.2022)

The course is primarily for master and advanced bachelor students.