Przetwarzanie i wizualizacja danych (PWD)

Wykłady:

1. Wykład 1 (Podstawy R), wywołania, Ankieta.txt
   • J. Palm (2024). Introduction to R.
   • R.W. Nahhas (2024). An Introduction to R for Research.
   • Nana Kim. Introduction to R.
2. Wykład 2 (Grafika w R), wywołania
   • M. Friendly (2015). Discrete Data Analysis with R. Chapman and Hall/CRC. Chapter 1: Introduction.
   • M. Friendly (2015). Discrete Data Analysis with R. Chapman and Hall/CRC. Chapter 2: Working with Categorical Data.
   • M. Friendly (2015). Discrete Data Analysis with R. Chapman and Hall/CRC. Chapter 3: Fitting and Graphing Discrete Distributions.
   • M. Friendly (2015). Discrete Data Analysis with R. Chapman and Hall/CRC. Chapter 4: Two-Way Contingency Tables.
   • M. Friendly (2015). Discrete Data Analysis with R. Chapman and Hall/CRC. Chapter 5: Mosaic Displays for n-Way Tables.
3. Wykład 3 (Programowanie w R), wywołania
   • G. Grolemund (2014). Hands-On Programming with R. O’Reilly Media.
   • R.D. Peng (2022). R Programming for Data Science.
   • H. Wickham (2019). Advanced R (2e). Chapman and Hall/CRC.
4. Wykład 4 (Biblioteki: tibble, tidyr, dplyr), wywołania
   • H. Wickham, M. Cetinkaya-Rundel, G. Grolemund (2023). R for Data Science (2e). O’Reilly Media.
5. Wykład 5 (Biblioteka ggplot2, mapy), wywołania
   • H. Wickham, D. Navarro, T.L. Pedersen. Elegant Graphics for Data Analysis (3e).
   • W. Chang (2018). R Graphics Cookbook (2e). O’Reilly Media.
   • C.O. Wilke (2019). Fundamentals of Data Visualization. O’Reilly Media.
   • R. Kabacoff (2024). Modern Data Visualization with R. Chapman and Hall/CRC.
   • V. Olaya. Introduction of GIS. Chapter: Visualization of geographical data.
   • R. Lovelace, J. Nowosad, J. Muenchow (2025). Geocomputation with R (2e). Chapman and Hall/CRC.
   • J. Nowosad. Geostatystyka w R.
   • P. Baumgartner (2025). Geographic Datascience with R.
   • P. Biecek. (2022). Wykresy od kuchni. Rozdział 6: Zakoduj to sam.
6. Wykład 6 (Biblioteki: lubridate, stringr, purrr), wywołania
7. Wykład 7 (Biblioteki: plotly, highcharter, morrisjs), wywołania
   • P. Baumgartner (2025). Learning Plotly.
8. Wykład 8 (Biblioteka shiny), wywołania
   • H. Wickham (2021). Mastering Shiny. O’Reilly Media.
   • C. Sievert (2019). Interactive web-based data visualization with R, plotly, and shiny. Chapman and Hall/CRC.

Ćwiczenia:

1. Ćwiczenia 1 & 2 (Podstawy R), Table1.txt, Table2.txt
2. Ćwiczenia 3 & 4 (Grafika w R)
3. Ćwiczenia 5 (Programowanie w R)
4. Ćwiczenia 6 & 7 (Biblioteki: tibble, tidyr, dplyr)
5. Ćwiczenia 8 & 9 (Biblioteka ggplot2, mapy)
6. Ćwiczenia 10 (Biblioteki: lubridate, stringr, purrr)
7. Ćwiczenia 11 (Biblioteki: plotly, highcharter, morrisjs)
8. Ćwiczenia 12 (Biblioteka shiny), usaUFOsightings.csv

Laboratoria

This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Learn any time, anywhere and become an expert in R, Python, SQL, and more. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 350+ courses by expert instructors on topics such as importing data, data visualization, and machine learning. They’re constantly expanding their curriculum to keep up with the latest technology trends and to provide the best learning experience for all skill levels. Join over 6 million learners around the world and close your skills gap.