Week 3
Data wrangling: Data import and manipulations
W03-00 Data Workflow + Tidy data + Wrangling
In class
- SLIDES: π₯W03-00 Data Workflow + Tidy data + Wrangling
- Recommended. Practice:
Primers: Programming basics
- Recommended. Read:
- Optional. Watch:
Tidy data video + slides- Grammar of data wrangling video + slides
webinar: Data wrangling with R and RStudio
W03-01 Import data
In class
- Application Exercise: π
ae03-01-import-clean-sum-plot.Rmd
SELF STUDY
- SLIDES: π₯W03-02 Import data
- Recommended. Watch:
- Recommended. Read:
- Optional. Read:
- CHEATSHEET: Data import with the tidyverse
- tidyverse/readxl + tidyverse/readr + janitor
- Optional. Watch:
- Importing and recoding data
- Data classes video + slides
- Importing data video + slides
- webinar: Whatβs new with readxl?
W03-02 Exploring numerical data
SELF STUDY
- SLIDES: π₯W03-02 Exploring numerical data
- Application Exercise: π
AE03-02 Exploring data on plstic waste+ Solution to the ae03-02:ae03-02-plastic-waste-solutions.rmd
- Recommended. Practice:
- Primers: Derive Information with dplyr
Open Intro. Interactive. Visualizing numerical data (takes time to load)- Open Intro. Interactive. Summarizing data (takes time to load)
- Primers: Data Visualization Basics
- Primers: Histograms
- Primers: Boxplots and Counts
- Primers: Scatterplots
- Optional. Read:
- Optional. Watch + Practice:
π₯ W03-03 Correlation
In class
- SLIDES: π₯W03-04 correlation correlation
SELF STUDY
- Application Exercise: π
ae03-03-correlation.Rmd
- Recommended. Practice:
- Primers: Exploratory data analysis
- Recommended. Read:
- Optional. Read:
π W03AE - application exercise:
Download project from π ae03-data-wrangling.zip or the same on Ilias: π ae03-data-wrangling.zip on Ilias.
In class
- Application Exercise: π
ae03-01-import-clean-sum-plot.Rmd
SELF STUDY
- Application Exercise: π
ae03-02-correlation.Rmd - Application Exercise: π
ae03-02-plastic-waste.rmd
π₯ SELF STUDY Exploring categorical data
- Recommended. Practice:
- Open Intro. Interactive. Visualizing categorical data (takes time to load)
- Recommended. Watch + Practice:
- webinar: Tidyverse visualization manipulation basics
- Visualising categorical data video + slides
- Optional. Read:
π₯ SELF STUDY Wrangle with dplyr
We use dplyr every day in any exercise. Thus, there is no point to dedicate specific time to it. Use this list of materials to guide your learning process. Most of the core functions of dplyr are covered in data other parts of the course.
Materials listed here may repeat the ones listed before.
Recommended. Read:
Recommended. Practice:
- Primers: Working with Tibbles
- Primers: Isolating Data with dplyr
- Primers: Derive Information with dplyr
- Primers: Filter observations
- Open Intro. Interactive. Summarizing data (takes time to load)
- Interactive tutorial based on R4DS Ch. 5.6 Summarizing data
π₯ SELF STUDY Data visualization with ggplot2
There are many ways how data could be visualized in R. We do touch numerous visualization examples over the course. Therefore, dedicated mastering of the ggplot2 package is scheduled for self learning.
- Recommended. Read:
- Recommended. Practice:
- Primers: Data Visualization Basics
- Primers: Exploratory data analysis
- Primers: Bar Charts
- Primers: Histograms
- Primers: Boxplots and Counts
- Primers: Scatterplots
- Primers: Overplotting
- Primers: Customize plots
- Optional. Practice:
- Open Intro. Interactive. Visualizing categorical data (takes time to load)
- Open Intro. Interactive. Visualizing numerical data (takes time to load)
- Optional. Watch + Practice: