r - Generating a histogram and density plot from binned data -


i've binned data , have dataframe consists of 2 columns, 1 specifies bin range , specifies frequency this:-

> head(data)       binrange frequency 1    (0,0.025]        88 2 (0.025,0.05]        72 3 (0.05,0.075]        92 4  (0.075,0.1]        38 5  (0.1,0.125]        20 6 (0.125,0.15]        16

i want plot histogram , density plot using can't seem find way of doing without having generate new bins etc. using solution here tried following:-

p <- ggplot(data, aes(x= binrange, y=frequency)) + geom_histogram(stat="identity")

but crashes. know of how deal this?

thank you

the problem ggplot doesnt understand data way input it, need reshape (i not regex-master, surely there better ways is):

df <- read.table(header = true, text = "                  binrange frequency 1    (0,0.025]        88 2 (0.025,0.05]        72 3 (0.05,0.075]        92 4  (0.075,0.1]        38 5  (0.1,0.125]        20 6 (0.125,0.15]        16")  library(stringr) library(splitstackshape) library(ggplot2) # extract numbers out, df$binrange <- str_extract(df$binrange, "[0-9].*[0-9]+")  # split data using , columns: # 1 start-point , 1 end-point df <- csplit(df, "binrange")  # plot it, dont need second column ggplot(df, aes(x = binrange_1, y = frequency, width = 0.025)) +     geom_bar(stat = "identity", breaks=seq(0,0.125, by=0.025))

or if don't want data interpreted numerically, can following:

df <- read.table(header = true, text = "                  binrange frequency 1    (0,0.025]        88 2 (0.025,0.05]        72 3 (0.05,0.075]        92 4  (0.075,0.1]        38 5  (0.1,0.125]        20 6 (0.125,0.15]        16")  library(ggplot2) ggplot(df, aes(x = binrange, y = frequency)) + geom_bar(stat = "identity")

you won't able plot density-plot data, given not continous rather categorical, thats why prefer second way of showing it,


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