Creating a line graph using ggplot2 without a set "y"?

Question

I guess I am trying to create a geom_line version of a geom_bar. The reason I want to do lines is because when I enter

geom_bar(aes(fill = Decile), position = position_dodge())

I am stuck with ten segments and my bar chart looks extremely cluttered.
I have 11 separate x variables going across the bottom.
The problem is I dont know how to use the count as a "y" variable and have tried things like ..count.. and other approached but am completely lost. Any ideas?

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Thanks for the help!

My data looks like this:

Name Decile Division
Joe 1 San Diego
Jan 1 New York
Jay 2 San Diego
Lue 3 Dallas
Suz 2 Seattle
tye 3 Dallas

MCD <- read.csv("Decile15.csv", header = TRUE)

MCD$MonthNo <- factor(MCD$MonthNo, levels = c(1:11), labels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November"))

Decile_names <- c('1' = "Decile #1",
                '2' = "Decile #2",
                '3' = "Decile #3",
                '4' = "Decile #4",
                '5' = "Decile #5"
                 )





MCDGraph <- ggplot(na.omit(MCD), aes(MonthNo))

MCDGraph + geom_bar(aes(fill = Division), color = "black", position = "fill") +     facet_wrap(~Decile, nrow = 1, labeller = labeller(Decile = as_labeller(Decile_names))) + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5)) +     scale_fill_manual(values = c("#DA4424", "#24A0DA", "#F0BC0B", "#43F749", "#4348F7", "#F74369", "#D7B9F5")) + theme(panel.background = element_rect(colour = "black", fill = "white"), panel.grid.minor = element_line(color = "black", size = .5)) + labs(x = "2017", y = "% of Leads Per Month By Division") + scale_y_continuous(labels = percent_format()) + theme(strip.background = element_blank(), strip.text = element_text(size = 25))

This is what my % of grouped facet_wrap bar chart looked like.

I split those into 5 so that I could see five plots instead of 10 on one pdf sheet. Also this is only divided into the 7 total divisions. I want to do one that is divided into 10. Here is an example I used to make my grouped regular without faceting anything.

MC <- read.csv("2017_Full_year.csv", header = TRUE)

MC$MonthNo <- factor(MC$MonthNo, levels = c(1:11), labels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November"))



MCH <- ggplot(na.omit(MC), aes(MonthNo))

MCH + geom_bar(aes(fill = Division), position = position_dodge() ) + labs(x = "2017", y = "# of Leads") + theme(axis.line = element_line(color = "black", size = 3, linetype = "solid"), axis.text.x = element_text(face = "bold", color = "black", size = 14),
  axis.text.y = element_text(face = "bold", color = "black", size = 14)) + scale_y_continuous(name = "# Of Leads", breaks = seq(0,1000, 50)) + theme(panel.background = element_rect(colour = "black",
  fill = "white"), panel.grid.minor = element_line(color = "black", size = .5), panel.grid.major = element_line(color = "black", size = .5)) +
  scale_fill_manual(values = c("#DA4424", "#24A0DA", "#F0BC0B", "#43F749", "#4348F7", "#F74369","#D7B9F5"))

EDIT: Or should I just create a new csv with the the final counts for each Decile during each month already in it. This would be a quick fix and I can pull the numbers very easily from SQL server. I was just hoping to do this without having to create a new file.

Answer 1

Not sure how this would look with your real data, but something you could explore that looks nice in situations like these are ridgeplots using the ggrigdes package. Example is below:

  library(ggridges)
  library(dplyr)
  library(ggplot2)


  set.seed(99)

  MCD <- tibble(
                Name = sample(c("Joe", "Jay", "Susan", "Nancy", "Mark"), 1000, T),
                Decile = sample(1:10,1000, T) ,
                Division = sample(c('San Diego', 'New York', 'Dallas', 'Seattle', 'LA'), 1000, T),
                MonthNo = sample(1:11, 1000 , T))


  MCD$MonthNo <- factor(MCD$MonthNo, levels = c(1:11), labels = c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November"))

  MCD %>% group_by(Decile, MonthNo) %>% summarize(Count = n()) %>% 
       ungroup() %>%  mutate(Decile = factor(Decile)) %>%  
       ggplot(aes(x = MonthNo, y = Decile, height = Count, group = Decile, fill = Decile)) + 
       geom_density_ridges(alpha = 0.7, show.legend = F, stat = "identity", scale = 1)

Answer 2

This should get you the "geom_line version of geom_bar"

df <- data.frame(x=c(1,1,1, 3,3, 10,10,10,10))
ggplot(df, aes(x=x)) + geom_line(stat="count")

UPDATE: Here is the version based on the dataset from TBT8's answer

library(dplyr)
library(ggplot2)

set.seed(99)
#create dummy dataset 
MCD <- tibble(
Name = sample(c("Joe", "Jay", "Susan", "Nancy", "Mark"), 1000, T),
Decile = sample(1:10,1000, T) ,
Division = sample(c('San Diego', 'New York', 'Dallas', 'Seattle', 'LA'), 1000, T),
MonthNo = sample(1:11, 1000 , T))

MCD$MonthNo <- factor(MCD$MonthNo, levels = c(1:11), 
labels = c("January", "February", 
"March", "April", "May", 
"June", "July", "August", 
"September", "October", "November"))

#create a numeric months vector
MonthNum <- 1:11
names(MonthNum) <- levels(MCD$MonthNo)

#create a factor to be used for facets
MCD$DecileF <- factor(
  MCD$Decile, 
  levels=as.character(sort(unique(MCD$Decile),
                           decreasing = TRUE)))

ggplot(MCD, aes(x = MonthNum[MonthNo], col=DecileF)) + 
  geom_path(stat = "count") +
  #geom_point(stat = "count") + 
  facet_grid(DecileF~.) + 
  scale_x_discrete(name ="Month", limits=names(MonthNum))