254 lines
3.2 KiB
Plaintext
254 lines
3.2 KiB
Plaintext
Lesson 5
|
|
========================================================
|
|
|
|
### Multivariate Data
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Moira Perceived Audience Size Colored by Age
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Third Qualitative Variable
|
|
Notes:
|
|
|
|
```{r Third Qualitative Variable}
|
|
ggplot(aes(x = gender, y = age),
|
|
data = subset(pf, !is.na(gender))) + geom_histogram()
|
|
```
|
|
|
|
***
|
|
|
|
### Plotting Conditional Summaries
|
|
Notes:
|
|
|
|
```{r Plotting Conditional Summaries}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Thinking in Ratios
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Wide and Long Format
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Reshaping Data
|
|
Notes:
|
|
|
|
```{r}
|
|
install.packages('reshape2')
|
|
library(reshape2)
|
|
```
|
|
|
|
|
|
***
|
|
|
|
### Ratio Plot
|
|
Notes:
|
|
|
|
```{r Ratio Plot}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Third Quantitative Variable
|
|
Notes:
|
|
|
|
```{r Third Quantitative Variable}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Cut a Variable
|
|
Notes:
|
|
|
|
```{r Cut a Variable}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Plotting it All Together
|
|
Notes:
|
|
|
|
```{r Plotting it All Together}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Plot the Grand Mean
|
|
Notes:
|
|
|
|
```{r Plot the Grand Mean}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Friending Rate
|
|
Notes:
|
|
|
|
```{r Friending Rate}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Friendships Initiated
|
|
Notes:
|
|
|
|
What is the median friend rate?
|
|
|
|
What is the maximum friend rate?
|
|
|
|
```{r Friendships Initiated}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Bias-Variance Tradeoff Revisited
|
|
Notes:
|
|
|
|
```{r Bias-Variance Tradeoff Revisited}
|
|
|
|
ggplot(aes(x = tenure, y = friendships_initiated / tenure),
|
|
data = subset(pf, tenure >= 1)) +
|
|
geom_line(aes(color = year_joined.bucket),
|
|
stat = 'summary',
|
|
fun.y = mean)
|
|
|
|
ggplot(aes(x = 7 * round(tenure / 7), y = friendships_initiated / tenure),
|
|
data = subset(pf, tenure > 0)) +
|
|
geom_line(aes(color = year_joined.bucket),
|
|
stat = "summary",
|
|
fun.y = mean)
|
|
|
|
ggplot(aes(x = 30 * round(tenure / 30), y = friendships_initiated / tenure),
|
|
data = subset(pf, tenure > 0)) +
|
|
geom_line(aes(color = year_joined.bucket),
|
|
stat = "summary",
|
|
fun.y = mean)
|
|
|
|
ggplot(aes(x = 90 * round(tenure / 90), y = friendships_initiated / tenure),
|
|
data = subset(pf, tenure > 0)) +
|
|
geom_line(aes(color = year_joined.bucket),
|
|
stat = "summary",
|
|
fun.y = mean)
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Sean's NFL Fan Sentiment Study
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Introducing the Yogurt Data Set
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Histograms Revisited
|
|
Notes:
|
|
|
|
```{r Histograms Revisited}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Number of Purchases
|
|
Notes:
|
|
|
|
```{r Number of Purchases}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Prices over Time
|
|
Notes:
|
|
|
|
```{r Prices over Time}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### Sampling Observations
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Looking at Samples of Households
|
|
|
|
```{r Looking at Sample of Households}
|
|
|
|
```
|
|
|
|
***
|
|
|
|
### The Limits of Cross Sectional Data
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Many Variables
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Scatterplot Matrix
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Even More Variables
|
|
Notes:
|
|
|
|
***
|
|
|
|
### Heat Maps
|
|
Notes:
|
|
|
|
```{r}
|
|
nci <- read.table("nci.tsv")
|
|
colnames(nci) <- c(1:64)
|
|
```
|
|
|
|
```{r}
|
|
nci.long.samp <- melt(as.matrix(nci[1:200,]))
|
|
names(nci.long.samp) <- c("gene", "case", "value")
|
|
head(nci.long.samp)
|
|
|
|
ggplot(aes(y = gene, x = case, fill = value),
|
|
data = nci.long.samp) +
|
|
geom_tile() +
|
|
scale_fill_gradientn(colours = colorRampPalette(c("blue", "red"))(100))
|
|
```
|
|
|
|
|
|
***
|
|
|
|
### Analyzing Three of More Variables
|
|
Reflection:
|
|
|
|
***
|
|
|
|
Click **KnitHTML** to see all of your hard work and to have an html
|
|
page of this lesson, your answers, and your notes!
|
|
|