EDA - Spring 2020
Syllabus
Schedule
Readings
0: Course prep
1: Course introduction
2: Exploring data
3: Visualizing information
4: Graphing amounts & proportions
5: Graphing comparisons
6: Graphing trends
7: Data cleaning & joins
8: Polishing your charts
9: Maps & geospatial data
11: Correlation analysis
12: Shiny apps
13: Communicating your results
Assignments
0: Class prerequisites
1: Exploring data
2: Plotting with ggplot2
3: Plotting with factors
4: Wind power redesign
5: Data cleaning & joins
6: Maps & geo-spatial data
7: Redesign 2
Final project
Resources
Getting Help
Finding Data
Visualizing Data
Programming in R
R Markdown
Other
About
About
License
DataCamp
Slack
Showcase
Contact
GitHub
Programming in R
Programming in R
Last semester’s course website :)
Grolemund, Garrett. “Hands-On Programming with R” [
free online
], [
buy on amazon
]
Peng, Roger D. “R Programming for Data Science” [
online - pay what you want
]
Data Analysis in R
Grolemund, Garrett and Wickham, Hadley. “R for Data Science” [
free online
], [
buy on amazon
]
Peng, Roger D. “Exploratory Data Analysis with R” [
online - pay what you want
]
16 HOWTO’s
, by Lingyun Zhang
RMarkdown
Andrew Heiss’s Markdown guide
60 second markdown guide
10 minute markdown tutorial
Markdown It
: Quickly demo Markdown code.
Table generator
: Create tables and get export code for multiple formats.
CMU RMarkdown guide (very detailed)
RStudio “Cheatsheets”
All cheatsheets
Data wrangling with the
dplyr
library
Data visualization with the
ggplot2
library
RMarkdown
EMSE 4197 (CRN 78916): Exploratory Data Analysis - Spring 2020
George Washington University
|
School of Engineering & Applied Science
Dr. John Paul Helveston
|
jph@gwu.edu
|
Wednesdays |
12:45–3:15 PM |
District House B205 |
|
This work is licensed under a
Creative Commons ShareAlike 4.0 International License
.
See the
licensing
page for more details about copyright information.
Content
2020
John Paul Helveston