ggplot y axis totals from data frame editing

[Dan0o0o]

Newbie here....in ggplot I am coming across a thing I haven't been able to remedy. Code is below with dataframe screenshotted that I am mapping to.

How can I edit it so the Y axis does NOT TOTAL UP NumSP column for each team? For example, the 1997 ANA used 11 NumSP for the season. That is the only number (11) I want in Y axis on ggplots, not multiplying 11 x 11 for each pitcher that distinctly pitched on that team for a total of 121 which it is summing in my code below for y axis.

I realize my dataframe is off and how could I use dplyr to select only a row from each team and year, uniquely? or is there a way to do it in ggplot with the stat = "identity" area?

appreciate any guidance!

'''ggplot(data = FinalGS, mapping = aes(x = yearID, y = NumSP, color = teamID))+
geom_bar(stat = "identity")+
labs(title = "Amount of Total Starters Used per Team, 1990-2021")+
ylab ("Number of Starting Pitchers")+
xlab("Year")+
theme(axis.title.y = element_text(color="#993333", size=13, face="bold"))+
theme(axis.title.x = element_text(color="#993333", size=13, face="bold"))+
theme(plot.title = element_text(color="Dark Red", size=14, face="bold.italic"))+
theme(axis.text.x = element_text(color = "dark red", size = 9, face ="bold"))'''

[FactOREO]

Hey,

welcome in the forum. Please provide your data (e.g. your data from the screenshot) as reproducible example, so that other users can easier reproduce your problem and help finding a solution.

[M_AcostaCH]

Check this for make a reproducible example. It is important for find a better help of all community.

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

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.…

Other way is paste the result when you put this in the console.

dput(FinalGS [1:40 , ] )

[Dan0o0o]

Thanks for that...here is more of my reproducible code below...

The issue is on the FinalGS DataFrame with screenshot below....it lists EVERY playerID that appeared in a game for that team. NumSP is the column I need to y axis of ggplots...how do I reduce every unique playerID to just ONE row per team in the FinalGS dataframe?

library(Lahman)
library(tidyverse)
library(dplyr)
library(tidyr)
library(purrr)
library(ggrepel)
View(LahmanData)
View(Pitching)
View(Teams)
Totals = merge(Teams, Pitching, by=c("yearID","teamID"))
View(Totals)

#To see how many total pitchers had a GS on the 2011 Milwaukee Brewers, 6 total
MIL <- filter(Totals, yearID == 2011, teamID == "MIL", GS > 0)
View(MIL)
#This below lists any pitcher with a GS on a club from 1990-2021, throwing 2022 out as the season is not complete
GSPitching1 <- filter(Totals, yearID < 2022, yearID >1989)
as_tibble(GSPitching1)
View(GSPitching1)

#This below is using dplyr group by and summarize to get INDIVIDUAL arms that has a GS in TeamGSUSE dataFrame
teamGSUSE <- GSPitching1 %>% 
  select(yearID, teamID, playerID, G.x, GS, W.x, L.x, ERA.x) 
View(teamGSUSE)             
TeamGS <- GSPitching1 %>% 
  group_by(yearID, teamID) %>% 
  summarise(TGS = sum(GS))
head(TeamGS)
View(TeamGS)
head(teamGSUSE)
View(teamGSUSE)
library(utils)
##The issue here is bringing TGS from TeamGS over to teamGSUSE b/c there are differing column totals
#for total number of teams and total number of pitchers. e.g. 13 man pitching staffs for 1 team
#solved w/ join on 2 variables below
library(base)
#This below works to merge them ON TWO COLUMNS
merged <-merge(TeamGS, teamGSUSE, by = c('teamID', 'yearID'))

View(merged)

#This below creates a new DataFrame where a pitcher started a game/had a GS in that season, throws out 100% relief pitchers
GSmerged <- filter(merged, GS > 0)
View(GSmerged)

#Stumbled here and figured it out (hat tip to "ML")
# By TEAM and YEAR. Then COUNT N() 
#Pipe then summarize number starts = n (). This works below!
#n() counts up the values into a new column
newmerged <- GSmerged %>% 
  group_by(teamID, yearID, ) %>% 
  summarise(NumSP = n())
View(newmerged)

#This merged the last two DataFrames into one for analysis and ggplot use with team stats and individual GS numbers by staff

FinalGS <-merge(newmerged, GSmerged, by = c('teamID', 'yearID'))

View(FinalGS)