Adding Layers to a Plot (ggplot)

Davia_Downey · March 29, 2021, 6:22pm

I have 3 piece of data that I need to layer onto one plot. The first time series layer is coded: p<-ggplot(MI_FL_Data, aes(realdate, FLday))+geom_line() The next layer adds two geom_hlines at yintercept=15000 and 17000 respectively. This layer is coded: q<-ggplot(MI_FL_Data, aes( realdate, FL_Actions))+geom_point(na.rm = TRUE) The final layer plots the points based on a categorical variable FL_Actions at the yintercept produced in the second code. This code is: r<-ggplot(MI_FL_Data, aes(realdate, FLday))+geom_hline(data = MI_FL_Data %>% filter(FL_Actions == 1), aes(yintercept = 15000), linetype=5, na.rm=TRUE)+ geom_hline(data = MI_FL_Data %>% filter(FL_Actions == 2), aes(yintercept = 17000), linetype=1, na.rm=TRUE))

Now I need to layer each of these saved vectors on top of each other in one graph. When I use the code: ggplot(MI_FL_Data, aes(realdate, FLday))+geom_hline(data=r)+geom_point(data=r) I get an error: data must be a data frame, or other object coercible by fortify() , not an S3 object with class gg/ggplot. I thought by saving each layer it would be fairly simple to just add them together. Any advice? I'm a bit of a novice with ggplot but what I want to do seems fairly intuitive so I'm stumped.

Here is the dput: dput(head(MI_FL_Data, 30))
structure(list(Date = c("1/22/20", "1/23/20", "1/24/20", "1/25/20",
"1/26/20", "1/27/20", "1/28/20", "1/29/20", "1/30/20", "1/31/20",
"2/1/20", "2/2/20", "2/3/20", "2/4/20", "2/5/20", "2/6/20", "2/7/20",
"2/8/20", "2/9/20", "2/10/20", "2/11/20", "2/12/20", "2/13/20",
"2/14/20", "2/15/20", "2/16/20", "2/17/20", "2/18/20", "2/19/20",
"2/20/20"), Date2 = c("1/22/20", "1/23/20", "1/24/20", "1/25/20",
"1/26/20", "1/27/20", "1/28/20", "1/29/20", "1/30/20", "1/31/20",
"2/1/20", "2/2/20", "2/3/20", "2/4/20", "2/5/20", "2/6/20", "2/7/20",
"2/8/20", "2/9/20", "2/10/20", "2/11/20", "2/12/20", "2/13/20",
"2/14/20", "2/15/20", "2/16/20", "2/17/20", "2/18/20", "2/19/20",
"2/20/20"), Date3 = c("1/22/20", "1/23/20", "1/24/20", "1/25/20",
"1/26/20", "1/27/20", "1/28/20", "1/29/20", "1/30/20", "1/31/20",
"2/1/20", "2/2/20", "2/3/20", "2/4/20", "2/5/20", "2/6/20", "2/7/20",
"2/8/20", "2/9/20", "2/10/20", "2/11/20", "2/12/20", "2/13/20",
"2/14/20", "2/15/20", "2/16/20", "2/17/20", "2/18/20", "2/19/20",
"2/20/20"), FLORIDA = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), FLday = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), MICHIGAN = c(0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0), MIday = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), FL_Actions = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_), MI_Actions = c(NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), realdate = structure(c(18283,
18284, 18285, 18286, 18287, 18288, 18289, 18290, 18291, 18292,
18293, 18294, 18295, 18296, 18297, 18298, 18299, 18300, 18301,
18302, 18303, 18304, 18305, 18306, 18307, 18308, 18309, 18310,
18311, 18312), class = "Date")), row.names = c(NA, -30L), class = c("tbl_df",
"tbl", "data.frame")) Note: the FL_Actions and MI_Actions columns do not have 1 2 coding because policies were not created until March

Here is the tibble from another date range: A tibble: 22 x 10 Date Date2 Date3 FLORIDA FLday MICHIGAN MIday FL_Actions MI_Actions realdate <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <date> 1 3/6/20 3/6/20 3/6/20 3 0 0 0 NA NA 2020-03-06 2 3/7/20 3/7/20 3/7/20 7 4 0 0 NA NA 2020-03-07 3 3/8/20 3/8/20 3/8/20 10 3 0 0 NA NA 2020-03-08 4 3/9/20 3/9/20 3/9/20 13 3 0 0 1 NA 2020-03-09 5 3/10/20 3/10/20 3/10/20 15 2 0 0 NA 1 2020-03-10 6 3/11/20 3/11/20 3/11/20 24 9 2 2 1 NA 2020-03-11 7 3/12/20 3/12/20 3/12/20 30 6 3 1 NA NA 2020-03-12 8 3/13/20 3/13/20 3/13/20 45 15 22 19 NA NA 2020-03-13 9 3/14/20 3/14/20 3/14/20 64 19 35 13 NA NA 2020-03-14 10 3/15/20 3/15/20 3/15/20 100 36 45 10 NA NA 2020-03-15

Finally, I was provided another code possibility on StackOverflow:
ggplot(MI_FL_Data, aes(realdate, FLday)) + geom_line()+ geom_label(data=MI_FL_Data, aes(label=FL_Actions), nudge_x = 0.50, nudge_y=.25, size=2, na.rm=TRUE)+geom_point(aes(realdate, 17000),na.rm = TRUE) + geom_point(aes(realdate, 15000), na.rm = TRUE) + geom_hline(data = MI_FL_Data %>% filter(FL_Actions == 1),aes(yintercept = 15000), linetype=5, na.rm=TRUE) +geom_hline(data = MI_FL_Data %>% filter(FL_Actions == 2),aes(yintercept = 17000), linetype=1, na.rm=TRUE)+labs(x=NULL, y="Number of Reported Daily COVID Cases", title="State of Florida",caption="1= closing actions, 2= opening actions")+theme_classic()

This code produces this image and as you can see, the 1 2 codes are on the timeseries line and not the geom_hlines where I need them.

nirgrahamuk · March 29, 2021, 8:46pm

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners Guides & FAQs

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

Short Version

You can share your data in a forum friendly way by passing the data to share to the dput() function.
If your data is too large you can use standard methods to reduce it before sending to dput().
When you come to share the dput() text that represents your data, please be sure to format your post with triple backticks on the line before your code begins to format it appropriately.

```
( example_df <- structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 
5, 4.4, 4.9), Sepal.Width = c(3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 
3.4, 2.9, 3.1), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 
1.4, 1.5, 1.4, 1.5), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 
0.4, 0.3, 0.2, 0.2, 0.1), Species = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("setosa", "versicolor", "virginica"
), class = "factor")), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame")))
```

Davia_Downey · March 29, 2021, 9:24pm

I was able to adjust the code by adding a y=15500 to the label. However, there is still a bolded line that's being overlaid on the remaining hline. If any contributors have ideas as to how to eliminate the overlay I would appreciate it.

gplot(MI_FL_Data, aes(realdate, FLday)) + geom_line()+ geom_label(data=MI_FL_Data, aes(label=FL_Actions), na.rm=TRUE, y=15500)+ geom_point(aes(realdate, 15000), na.rm = TRUE) + geom_hline(data = MI_FL_Data %>% filter(FL_Actions >= 1),aes(yintercept = 15000), linetype=5, na.rm=TRUE)+labs(x=NULL, y="Number of Reported Daily COVID Cases", title="State of Florida",caption="1= closing actions, 2= opening actions")+theme_classic()

system · April 19, 2021, 9:24pm

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