Restructure csv data for r and ggplot2 - r

Question

I'm new to R and ggplot2. I have a csv file with beverage consumption data. The first column is the Year, and then the next 9 columns are beverage types like, coffee, tea, soda, etc., with values for the consumption amount for the year value of that row. The data covers a 41 year period. I've been researching this and trying many things. I can easily create a dot plot for any one type of beverage with ggplot.
However, I want to create horizontal stacked dot plots with Year on the x axis for each plot. So, there'd be a plot for coffee, and then right below it, one for tea, etc. I think I want to use facets. I'm also thinking I want to get my data restructured so it has 3 columns: one for year, one for "category" (i.e., coffee, tea, soda, etc.), and the last one for the value. My thinking is that once I get the data in that form, then using faceting should be straight forward.
Problem is, I can't seem to figure out how to get my data in that form. Here is how the first few rows of the data look:
Year Whole Milk Other Milk Total Milk Tea Coffee Diet Soda Regular Soda Total Soda Juice
1970 25.5 5.8 31.3 6.8 33.4 2.1 22.2 24.3 5.5
1971 25 6.3 31.3 7.2 32.2 2.2 23.3 25.5 5.8
1972 24.1 6.9 31 7.3 33.6 2.3 23.9 26.2 6
Can someone help me?
dput of the data is:
structure(list(Year = 1970:1972, `Whole Milk` = c(25.5, 25, 24.1
), `Other Milk` = c(5.8, 6.3, 6.9), `Total Milk` = c(31.3, 31.3,
31), Tea = c(6.8, 7.2, 7.3), Coffee = c(33.4, 32.2, 33.6), `Diet Soda` = c(2.1,
2.2, 2.3), `Regular Soda` = c(22.2, 23.3, 23.9), `Total Soda` = c(24.3,
25.5, 26.2), Juice = c(5.5, 5.8, 6)), .Names = c("Year", "Whole Milk",
"Other Milk", "Total Milk", "Tea", "Coffee", "Diet Soda", "Regular Soda",
"Total Soda", "Juice"), class = "data.frame", row.names = c(NA,
-3L))

Answer 1

I have a little saying that I use often for ggplot2, "When in doubt, melt". In the reshape package there is a function melt(), that does exactly this.
tmp <- structure(list(Year = 1970:1972, `Whole Milk` = c(25.5, 25, 24.1
), `Other Milk` = c(5.8, 6.3, 6.9), `Total Milk` = c(31.3, 31.3,
31), Tea = c(6.8, 7.2, 7.3), Coffee = c(33.4, 32.2, 33.6), `Diet Soda` = c(2.1,
2.2, 2.3), `Regular Soda` = c(22.2, 23.3, 23.9), `Total Soda` = c(24.3,
25.5, 26.2), Juice = c(5.5, 5.8, 6)), .Names = c("Year", "Whole Milk",
"Other Milk", "Total Milk", "Tea", "Coffee", "Diet Soda", "Regular Soda",
"Total Soda", "Juice"), class = "data.frame", row.names = c(NA,
-3L))
library(reshape)
melt(tmp, id.vars="Year")
Year variable value
1 1970 Whole Milk 25.5
2 1971 Whole Milk 25.0
3 1972 Whole Milk 24.1
4 1970 Other Milk 5.8
5 1971 Other Milk 6.3
6 1972 Other Milk 6.9
7 1970 Total Milk 31.3
8 1971 Total Milk 31.3
9 1972 Total Milk 31.0
10 1970 Tea 6.8
11 1971 Tea 7.2
12 1972 Tea 7.3
13 1970 Coffee 33.4
...