### list.files("data/week_03") # just take a look around
### w3.data <- read.csv("data/week_03/group_01.csv")
-w3.data <- read.csv(url("https://communitydata.cc/~ads/teaching/2019/stats/data/week_03/group_02.csv"))
+w3.dtata <- read.csv(url("https://communitydata.cc/~ads/teaching/2019/stats/data/week_03/group_02.csv"))
```
### PC3. Get to know your data!
I can create a table comparing the sorted rounded values to check this.
```{r}
-table(sort(round(w2.data, 6)) == sort(round(w3.data$x, 6)))
+table(round(w2.data,6) == round(w3.data$x,6))
```
Can you explain what each piece of that last line of code is doing?
lapply(w3.data, summary)
### Run this line again to assign the new dataframe to p
-p <- ggplot(w3.data, aes(x=x, y=y))
+p <- ggplot(data=w3.data, mapping=aes(x=x, y=y))
p + geom_point(aes(color=j, size=l, shape=k))
```
<pre><code>## [1] 9.643215 2.158358 1.396595 0.192623 1.752234 0.170634</code></pre>
<p>Inspecting the first few values returned by <code>head()</code> gave you a clue. Rounded to six decimal places, the vectors match!</p>
<p>I can create a table comparing the sorted rounded values to check this.</p>
-<pre class="r"><code>table(sort(round(w2.data, 6)) == sort(round(w3.data$x, 6)))</code></pre>
+<pre class="r"><code>table(round(w2.data,6) == round(w3.data$x,6))</code></pre>
<pre><code>##
## TRUE
## 95</code></pre>
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## -4.42 3.19 7.81 9.96 14.61 33.14 5</code></pre>
<pre class="r"><code>### Run this line again to assign the new dataframe to p
-p <- ggplot(w3.data, aes(x=x, y=y))
+p <- ggplot(data=w3.data, mapping=aes(x=x, y=y))
p + geom_point(aes(color=j, size=l, shape=k))</code></pre>
<pre><code>## Warning: Using size for a discrete variable is not advised.</code></pre>