The course syllabus (and setup instructions) can be found here.
- Friday 5/13 Note on the ethics of Open Data Science
- Monday 5/9
- Delaney's presentation.
- Course feedback survey.
- Friday 5/6
- No Lecture. Doodle poll for signing up to open office hours.
- HW-4 Discussion
- In lab discussion
- Files. Please save these files in your
HW-4
folder and Knit. Don't forget to ensure you have all necessary packages. If this doesn't work, you can follow along here.
- Monday 5/2
- No Lecture. Doodle poll for signing up to open office hours.
- Friday 4/29
- No Lecture. Doodle poll for signing up to open office hours.
- HW-5. Also a few final examples of text mining:
- Latent Dirichlet Allocation
- Using
tm
andlda
packages: Federalist Papers
- Lec22: tm Package
- Files:
- Slides: Text Mining Package.
Lec22.R
Exercise.
- Remaining schedule
- Wed 4/27: HW-5 assigned
- Fri 4/29 and Mon 5/2: No lecture, but rather open office hours. Please send an email to schedule.
- Wed 5/4: HW-4 discussion in Wilson Lab.
- Fri 5/6: No lecture, but rather open office hours. Please send an email to schedule.
- Mon 5/9 through Mon 5/16: Presentations.
- Files:
- Lec21: Twitter Data
- Files:
- Slides: Twitter Data.
Lec21.R
Exercise.
- Files:
- HW-3 Discussion
- In lab discussion
- Files
HW-3_Albert_Notes.Rmd
. Please save this file in yourHW-3
folder and Knit. Don't forget to ensure you have all necessary packages. If this doesn't work, you can follow along here.
- Lec20: Final Project and String Manipulation
- Final Project GitHub repo to be forked is available. Please submit your projects there.
- Files:
- Slides: String Manipulation.
Lec20.R
Exercise.
- HW-4
- Also determined order of presentations using
presentations.R
in theMisc
folder and Enrique's favorite number 7 as the random number generator seed value.
- Also determined order of presentations using
Monday 5/9 | Wednesday 5/11 | Friday 5/13 | Monday 5/16 |
---|---|---|---|
Shaojin | Alison | Kyler | Joy |
Delaney | Andrew | Enrique | Philip |
Aminata | Jacob | Mo | Carter |
Christian | Paul |
- Lec19: Spatial Autocorrelation
- Files:
- Slides: Spatial Autocorrelation.
Lec19.R
Exercise.tract2010.zip
zip file of Multnomah Country, Oregon shapefiles.- Near and Far
- Files:
- Lec18: Leaflet Package
- Files:
- Slides: Open Street Map, Leaflet.
Lec18.R
Exercise.
- Files:
- HW-2 Discussion
- In lab discussion
- Files
HW-2_Albert_Notes.Rmd
. Please save this file in yourHW-2
folder and Knit. Don't forget to ensure you have all necessary packages. If this doesn't work, you can follow along here.
- Lec17: GIS and Shapefiles
- Files:
- Guest lecture by Patrick
Culbert
Teaching Fellow in Geography:
GIS_Raster_Vector.pdf
Lec17.R
Exercise.
- Guest lecture by Patrick
Culbert
Teaching Fellow in Geography:
- Files:
- Lec16: Shiny
- Slides: Shiny.
- Files:
Lec14_lubridate_solutions.R
Solutions. - Other:
- xkcd on GitHub.
datacamp.com
resource for learning R/Python in browser.
- Lec14: Packages & Vignettes and Finishing Dates & Times
- Slides: Hadleyverse, R Packages, and Vignettes.
- Files:
Lec14.R
Exercise.- Example of 3D plot using
plotly
:3D_plot_ex.Rmd
- Lec13: Final Project and Dates & Times with
lubridate
- Final project guidelines. Your project proposal is due Wednesday April 6th (after break) at 11:15.
- Open this Quandl link.
- Files:
Lec13.R
Exercise from "Lec13: Dates and Times with lubridate" folder.
- HW-1 Discussion
- In lab discussion
- Files:
HW-1_Albert_Notes.Rmd
from theHW-1
folder. - Setup:
- Save
HW-1_Albert_Notes.Rmd
in yourHW-1
project folder. - If you haven't already, install the
DT
,knitr
, andplotly
packages. - Load the datasets in your console.
- Save
- Lec11: Even More Logistic Regression
- In-class Lecture
- Files:
Lec11.R
Exercise.
- Lec10: More Logistic Regression
- In-class Lecture
- Lec09: Logistic Regression and OkCupid Data
- In-class Lecture and Slides
- Files:
Lec09.R
Exercise.- OkCupid Data CSV
- Lec08: More Regression
- In-class Lecture and Slides
- Files:
Lec08.R
Exercise.
- Lec07: Regression to the Mean
- In-class Lecture
- Files:
Lec07.R
Exercise.
- Lec06: Finishing
ggplot2
and Tidy Data usingtidyr
- Lec05: R Markdown and More
ggplot2
- Slides: Markdown and R Markdown
- Slides: More ggplot2
- Link to R Markdown Debugging Checks
- Files:
Lec05.R
Exercise.
- Lec04:
ggplot2
Package- Slides: More components of a statistical graphic and other ressources.
- Files:
Lec04.R
Exercise.
- Lec03:
dplyr
Joins- Slides:
dplyr
joins for merging data frames. - Files:
Lec03.R
Exercise.states.csv
. Click onRaw
button, then Save Page Asstates.csv
and notstates
.
- Slides:
- Grammar of Graphics
- Slides: Discussion on The Grammar of Graphics paper.
- Files:
babynames.Rmd
. Example of Shiny app (interactive visualization); installshiny
and listed packages first.
- Lec02: Loading Data
- Slides: The importance of minimizing prerequisites to research, loading data into RStudio via CSV files or webscraping.
- Files:
Lec02.R
Exercise. To download:- Go to the above directory "Lec02 Loading Data"
- Click on
Lec02.R
-> Raw - From your browser's menu bar -> File -> Save Page As... Be sure to save as
Lec02.R
and notLec02.R.txt
UCBAdmissions.xlsx
Excel spreadsheet. To download repeat steps a. and b. above.
- HW-0, due Wednesday 2016/2/24, is posted. This is merely a practice homework to familiarize yourselves to the HW submission format and process.
- Lec01: Data manipulation with
dplyr
- Slides: Tidy data, data manipulation verbs, piping
%>%
with themagrittr
package. - Files:
Lec01.R
Exercise
- Slides: Tidy data, data manipulation verbs, piping
- Lec00: Intro to Data Science
- Slides: What is data science? Building our data toolbox.