Writing a loop to create ggplot figures with different data sources and titles

Question

I do not have experience with loops but it looks like I will need to create some of them to analyze my data properly. Could you show how to create a simple loop on the code which I already created ? Let's use looping to get some plots:

pdf(file = sprintf("complex I analysis", tbl_comp_abu1), paper='A4r')

ggplot(df_tbl_data1_comp1, aes(Size_Range, Abundance, group=factor(Gene_Name))) +
  theme(legend.title=element_blank()) +
  geom_line(aes(color=factor(Gene_Name))) +
  ggtitle("Data1 - complex I")+
  theme(axis.text.x = element_text(angle = 90, hjust = 1))

ggplot(df_tbl_data2_comp1, aes(Size_Range, Abundance, group=factor(Gene_Name))) +
  theme(legend.title=element_blank()) +
  geom_line(aes(color=factor(Gene_Name))) +
  ggtitle("Data2 - complex I")+
  theme(axis.text.x = element_text(angle = 90, hjust = 1))


ggplot(df_tbl_data3_comp1, aes(Size_Range, Abundance, group=factor(Gene_Name))) +
  theme(legend.title=element_blank()) +
  geom_line(aes(color=factor(Gene_Name))) +
  ggtitle("Datas3 - complex I")+
  theme(axis.text.x = element_text(angle = 90, hjust = 1))

dev.off()

The question now is what I would like to achieve. So first of all I have like 10 complexes to analyze so that means 10 pdf files should be created and the example shows plots from three different data sets for the complex one. To make it properly the number in variable comp1 (from df_tbl_dataX_comp1) has to be changed from 1 to 10 - depends which complex we want to plot. The next thing which has to be changed through the loop is the name of pdf file and each of graphs... Is it possible to write such loop ?

Data:

structure(list(Size_Range = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 
3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 
8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 
13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 
17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L), .Label = c("10", 
"34", "59", "84", "110", "134", "165", "199", "234", "257", "362", 
"433", "506", "581", "652", "733", "818", "896", "972", "1039"
), class = "factor"), Abundance = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 142733.475, 108263.525, 98261.11, 649286.165, 
3320759.803, 3708515.148, 6691260.945, 30946562.92, 180974.3725, 
4530005.805, 21499827.89, 0, 15032198.54, 4058060.583, 0, 3842964.97, 
2544030.857, 0, 1640476.977, 286249.1775, 0, 217388.5675, 1252965.433, 
0, 1314666.05, 167467.8825, 0, 253798.15, 107244.9925, 0, 207341.1925, 
15755.485, 0, 71015.85, 14828.5075, 0, 25966.2325, 0, 0, 0, 0, 
0, 0), Gene_Name = c("AT1G01080", "AT1G01090", "AT1G01320", "AT1G01420", 
"AT1G01470", "AT1G01560", "AT1G01800", "AT1G02150", "AT1G02500", 
"AT1G02560", "AT1G02780", "AT1G02880", "AT1G02920", "AT1G02930", 
"AT1G03030", "AT1G03090", "AT1G03110", "AT1G03130", "AT1G03220", 
"AT1G03230", "AT1G03330", "AT1G03475", "AT1G03630", "AT1G03680", 
"AT1G03870", "ATCG00420", "ATCG00470", "ATCG00480", "ATCG00490", 
"ATCG00500", "ATCG00650", "ATCG00660", "ATCG00670", "ATCG00740", 
"ATCG00750", "ATCG00842", "ATCG01100", "ATCG01030", "ATCG01114", 
"ATCG01665", "ATCG00770", "ATCG00780", "ATCG00800", "ATCG00810", 
"ATCG00820", "ATCG00722", "ATCG00744", "ATCG00855", "ATCG00853", 
"ATCG00888", "ATCG00733", "ATCG00766", "ATCG00812", "ATCG00821", 
"ATCG00856", "ATCG00830", "ATCG00900", "ATCG01060", "ATCG01110", 
"ATCG01120")), .Names = c("Size_Range", "Abundance", "Gene_Name"
), row.names = c(NA, -60L), class = "data.frame")

Answer 1

This might do the trick: Initiate two loops, one for the complex iteration and a second for the dataset iteration. Then use paste0() or paste() to generate the correct filenames and headings.

PS.: I didn't test the code, since I dont have your data. But it should give you an idea.

#loop over complex    
for (c in 1:10) {

    #create pdf for every complex 
    pdf(file = paste0("complex", c, "analysis.pdf"), paper='A4r')

    #loop over datasets
    for(d in 1:3) {

    #plot
    ggplot(get(paste0("df_tbl_data",d,"_comp",c)), aes(Size_Range, Abundance, group=factor(Gene_Name))) +
      theme(legend.title=element_blank()) +
      geom_line(aes(color=factor(Gene_Name))) +
      ggtitle(paste0("Data",d," - complex ",c))+
      theme(axis.text.x = element_text(angle = 90, hjust = 1))
    }   
    dev.off()

}