I am trying to make a graph with the mean of trash collected of the multiple data sets but unsuccessful .

Trash collected dump truck shif 1,mapa 1,2,3

DUMPT1_1 <- filter(data8,TC %in% "DUMPT",shift2 %in% "1",MAP %in% "1")#turno1 , mapa1
DUMPT1_2 <- filter(data8,TC %in% "DUMPT",shift2 %in% "1",MAP %in% "2")#turno1 , mapa2
DUMPT1_3 <- filter(data8,TC %in% "DUMPT",shift2 %in% "1",MAP %in% "3")#turno1 , mapa3
#trash collected dump truck second shift 2 mapa 1,2,3
DUMPT2_1 <- filter(data8,TC %in% "DUMPT",shift2 %in% "2",MAP %in% "1")#turno 2 mapa 1
DUMPT2_2 <- filter(data8,TC %in% "DUMPT",shift2 %in% "2",MAP %in% "2")#turnoc2 mapa 2
DUMPT2_3 <- filter(data8,TC %in% "DUMPT",shift2 %in% "2",MAP %in% "3")#turno2 mapa 3

##trash collected compact truck shift 2,map 1,2,3
##turno 1 y dos para el compact truck .
COMPACT1_1 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "1",MAP %in%"1")#turno 2 mapa 1
COMPACT1_2 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "1",MAP %in% "2")#turno 2 mapa 2
COMPACT1_3 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "1",MAP %in% "3")#turno 2 mapa 3

###COMPACT ##shift 2
COMPACT2_1 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "2",MAP %in%"1")#turno 2
COMPACT2_2 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "2",MAP %in%"2")
COMPACT2_3 <- filter(data8,TC %in% "COMPACTT",shift2 %in% "2",MAP %in%"3")

Mean of the Trash collected of file DUMPT_1...., AND COMPACT_1...

Trash_Collected_1 c(mean(DUMPT1_1$amount_of_thrash_collected),mean(DUMPT1_2$amount_of_thrash_collected),mean(DUMPT1_3$amount_of_thrash_collected))
Trash_Collected_2 <- c(mean(COMPACT1_1$amount_of_thrash_collected),mean(COMPACT1_2$amount_of_thrash_collected),mean(COMPACT1_3$amount_of_thrash_collected))

geom_line(aes(c(5,6,7),Trash_Collected_1,colour= TC ))+

xlab("tons")+ylab("trash Collected")

I ge this error Error in `geom_line()`:
! Problem while computing aesthetics.
ℹ Error occurred in the 1st layer.
Caused by error in `FUN()`:
! object 'TC' not found

but TC is in the data set DUMPT AND COMPACT

I think we need see moreyour code and some sample data.

A handy way to supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need. Just do dput(mydata) where mydata is your data. Copy the output and paste it here.

I recommend you back to basics and consider some simple ggplot2 examples. Ggplot2 needs a data= argument. You seem to be adding data.frames as entries in you aes statements. This is not how one uses ggplot2.

You seem to be trying to make multiple subsets of your main dataframe. You can use group_by() to achieve this, then calculate the means, save the results, and plot as a histogram with ggplot().
Something like this might work (but as stated above, we don't have access to a sample of your data):

data8 |> 
  group_by(TC, shift2, MAP) |> 
  summarise(m_amount = mean(amount_of_thrash_collected, na.rm=TRUE)) -> means_df

ggplot(means_df) +
  aes(y=m_amount) +

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