DCF Starter
======================

A quick introduction to data, cases, and variables.

You're meant to play around with this.

```{r include=FALSE}
require(DCF)
```

## Data Tables

Here are a few data tables.  Your task is to figure out what are the variables, what are the cases, and what kind of thing each variable is.

### Voter Registration

```{r}
data(WakeVotersSmall)
```

Let's focus on just a few variables:
```{r tidy=FALSE}
voters <- subset(WakeVotersSmall,
                 select=c("race","gender","party","Age",
                          "res_zip_code","name_sufx"))
```

Try `names()`, `nrow()`, `class()`, and `summary()` on the `voters` dataframe itself and on individual variables accessed, e.g., as `voters$race`.  Try `levels()` on individual variables.

* What type is each variable?
* What do you think the case is?  How might you confirm this?

### Bird Observations

```{r}
data(OrdwayBirdsOrig)
```

Again, focus on a few variables:
```{r tidy=FALSE}
birds <- subset(OrdwayBirdsOrig,
                select=c("Year","Month","Day","SpeciesName","Weight"))
```

Again, try `names()`, `nrow()`, `class()`, and `summary()` on the `birds` dataframe itself and on individual variables accessed, e.g., as `birds$Day`

* What do you think the case is?
* What type is each variable?
* Which variables are need cleaning?

### Derived from Bird Observations

Here's are two new dataframes derived from `birds`:
```{r}
one <- groupBy( birds, by=SpeciesName )
two <- groupBy( birds, by=list(SpeciesName,Month))
three <- groupBy( two, by=Month, total = sum(count))
```

For each of them, say what are the variables and what are the cases.