I would like to make a grouped bar plot. An example of my data is as follows:

```
site code year month gear total value
678490 2012 3 GL 13882
678490 2012 4 GL 50942
678490 2012 5 GL 54973
678490 2012 6 GL 63938
678490 2012 7 GL 23825
678490 2012 8 GL 8195
678490 2012 9 GL 14859
678490 2012 9 RT 3225
678490 2012 10 GL 981
678490 2012 10 RT 19074
678490 2012 11 SD 106384
678490 2012 11 RT 2828
678490 2012 12 GL 107167
678490 2012 12 RT 4514
```

There are 17 site code options, four year options, twelve month options, and four gear options.

What I would to produce is a plot per site, per year, showing the 'total value' for each gear, for each month, as a bar.

So far I have managed to produce a plot, specific to site and year, but with the total values displayed in one bar per month, not separated into separate bars per month (can not include image in first post!)

But for months 9, 10, 11 and 12 there were two gears used so I want there to be two bars for these months.

I am using the following piece of code:

```
ggplot(subset(cdata, year %in% c("2012") & site code %in% c("678490")),
aes(x = factor(month), y = total value)) +
geom_bar(stat = "identity") +
labs(x = "Month", y = "Total value")
```

Any help on this would be greatly appreciated.

Answer:

If you want separate bars for each `gear`

, then you should add `fill=gear`

to the `aes`

in `geom_bar`

:

```
ggplot(cdata[cdata$year==2012 & cdata$sitecode==678490,],
aes(x = factor(month), y = totalvalue, fill=gear)) +
geom_bar(stat = "identity", position="dodge") +
labs(x = "Month", y = "Total value")
```

this gives:

When you want to make a plot per site, per year, showing the 'total value' for each gear, for each month, as a bar, you can use `facet_grid`

. For example:

```
ggplot(cdata, aes(x = factor(month), y = totalvalue, fill=gear)) +
geom_bar(stat = "identity", position="dodge") +
labs(x = "Month", y = "Total value") +
facet_grid(sitecode ~ year)
```

this gives:

Some additional comments:

- It's probably better not to use spaces in your column names (in the code above I removed the spaces)
- Add an example to your question which illustrative for the problem you are facing. In this case, it's better to give an example dataset that includes several sitecodes and several years.

I therefore made up some data:

```
df1 <- read.table(text="sitecode year month gear totalvalue
678490 2012 3 GL 13882
678490 2012 4 GL 50942
678490 2012 5 GL 54973
678490 2012 6 GL 63938
678490 2012 7 GL 23825
678490 2012 8 GL 8195
678490 2012 9 GL 14859
678490 2012 9 RT 3225
678490 2012 10 GL 981
678490 2012 10 RT 19074
678490 2012 11 SD 106384
678490 2012 11 RT 2828
678490 2012 12 GL 107167
678490 2012 12 RT 4514", header= TRUE)
df2 <- df1
df2$sitecode <- 7849
df2$year <- 2013
df3 <- df1
df3$sitecode <- 7849
df4 <- df1
df4$year <- 2013
cdata <- rbind(df1,df2,df3,df4)
```

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