https://github.com/rudeboybert/math241

Reed College Data Science
https://github.com/rudeboybert/math241

Last synced: 13 days ago
JSON representation

Reed College Data Science

• Host: GitHub
• URL: https://github.com/rudeboybert/math241
• Owner: rudeboybert
• Created: 2015-01-23T18:50:10.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2016-03-23T14:55:51.000Z (over 8 years ago)
• Last Synced: 2024-10-09T22:06:28.921Z (about 1 month ago)
• Language: HTML
• Homepage:
• Size: 200 MB
• Stars: 6
• Watchers: 4
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd

Awesome Lists containing this project

README

        
---

title: "Case Studies in Statistical Analysis AKA Data Science"

output:

  html_document:

    keep_md: yes

---

This is the GitHub repository for Reed College's Spring 2015 MATH 241 Case Studies in Statistical Analysis AKA Data Science.  

* All slide presentations from this class can be found at [RPubs](http://rpubs.com/rudeboybert/) and is tagged: MATH 241.

* The syllabus can be found at [here](https://docs.google.com/spreadsheets/d/1HQPtHvPLQl_meSeJK372oXmkY7BVD4rCOamMSwTfaBI/pubhtml?gid=0&single=true).

* The summary presentation titled "Teaching Data Science to Undergrads: an ex-Googler’s Tales from the Trenches" can be found at [RPubs](http://rpubs.com/rudeboybert/Teaching_Data_Science_Ugrads).  The code to generate the slides can be found in the directory `Teaching_Data_Science_Ugrads`.

```{r, echo=FALSE, message=FALSE, warning=FALSE}

suppressPackageStartupMessages(library(ggplot2))

suppressPackageStartupMessages(library(dplyr))

suppressPackageStartupMessages(library(ggthemes))

```

                               

## Examples

### Flight data from Houston Airport (IAH)

Credit to Rennie Meyers

```{r, echo=FALSE, message=FALSE, fig.height=6}

flights <- read.csv("./Lec06 R Markdown + HW01/flights.csv", stringsAsFactors = FALSE) %>%

  tbl_df() %>%

  mutate(date=as.Date(date))

weather <- read.csv("./Lec06 R Markdown + HW01/weather.csv", stringsAsFactors = FALSE) %>%

  tbl_df() %>%

  mutate(date=as.Date(date))

planes <- read.csv("./Lec06 R Markdown + HW01/planes.csv", stringsAsFactors = FALSE) %>% 

  tbl_df()

airports <- read.csv("./Lec06 R Markdown + HW01/airports.csv", stringsAsFactors = FALSE) %>% 

  tbl_df()

states <- read.csv("./Lec06 R Markdown + HW01/states.csv", stringsAsFactors = FALSE) %>%

  tbl_df()

flight_delays <- flights %>% 

  select(date, dep_delay) %>%

  group_by(date)

flight_delays30 <- filter(flight_delays, dep_delay > 30) %>%

  count(date)

ggplot(data=flight_delays30, aes(x=date, y=n)) + 

  geom_line(stat="identity") +

  xlab("Date") + 

  ylab("Number of Flights Delayed longer than 30 minutes") +

  ggtitle("Departure Delays from Houston over a Year") +

  theme_economist() +

  geom_smooth(col="blue")

```

### Sex breakdown for different jobs on San Francisco OkCupid

Credit to Miguel Connor

```{r, echo=FALSE, message=FALSE, fig.width=10, fig.height=6}

profiles <- read.csv("./Lec09 OkCupid Data/profiles.csv", header=TRUE) %>% tbl_df()

ggplot(profiles, aes(job, fill = sex)) + 

  geom_bar(position = "dodge") + 

  xlab("Job") +

  ylab("Counts") +

  theme(axis.text.x=element_text(angle=45, hjust=1)) 

```

### Sex breakdown for different jobs on San Francisco OkCupid