Get All the Rows with Rownames Starting with Abc111

Get all the rows with rownames starting with ABC111

You could use e.g. substr or grepl:

df <- read.table(header=TRUE, row.names=1, sep=" ", text="col1 col2 col3 
ABC111001 12 12 13 
ABC111002 3 4 5 
ABC000111 7 6 1
ABC000112 9 23 1")

needle <- "ABC111"
i <- substr(row.names(df), 0, nchar(needle))==needle
i <- grepl(paste0("^", needle), row.names(df))
df[i,]
#           col1 col2 col3
# ABC111001   12   12   13
# ABC111002    3    4    5

How can I apply dplyr's select(,starts_with()) on rows, not columns?

I believe that the combination of dplyr's filter and the substring command are the most efficient:

library(dplyr)
filtered_df <- school %>% dplyr::filter(substr(Name,1,1) == "J")

How can i remove rows by condition (initial letters) in r?

You can also convert the data to a data frame and simply use filter() by the dpylr package. In addition to your code, you can have a solution like this:

Data <- data.frame(Data)

Then assign the filtered data to another dataframe.

DataFiltered <- Data %>% filter(Abbreviation %like% "SR_")

Similarly, you can use str_detect() function from stringr package for filtering. This works better, if there is a possibility that Abbreviation has entities having 'SR_' not only as the first 3 characters. You can use RegEx to specify that each entity in filtered data must have Abbreviation starting with 'SR_'.

DataFiltered <- Data %>% filter(str_detect(Abbreviation, pattern = "^SR_"))

R: converting tidyverse to dplyr/reshape2 for plots

Using only melt() from reshape2 as suggested by great comment of @qdread and some base R:

library(reshape2)
library(ggplot2)
#Code
Data$order <- rownames(Data)
Melted <- melt(Data,id.vars = c('order','ID','color'))
Melted$order <- as.numeric(Melted$order)
#Plot
G <- ggplot(Melted,aes(x = value, 
           y = order,  
           col = ID, 
           group = order)) +
  # Draw points
  geom_point()+
  # Draw lines
  geom_line() +
  # Maybe you want to remove the y axis title, text and ticks
  theme(axis.title.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        # I added a vertical format to the x axis labels 
        # it might easier to read this way
        axis.text.x = element_text(angle = 90, vjust = 0.5))

Output:

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