Please study each line of code, and use the str command to study the
intermediate data objects... the examples on this list are almost never
plug-and-play for your real work. Note that while you provided some of the
code necessary to make your example reproducible, I had to fill in blanks
with additional code... the Posting Guide asks you to make your example
run as-is to get us to the point where you are having problems. The below
code is a model for posing your future questions as well as an answer to
this one.
library(ggplot2)
DF1 <- read.table( text =
"case size
case1 120
case2 120
case3 121
case4 121
case5 121
case6 122
case7 122
case8 123
", header=TRUE, as.is=TRUE )
# note the fewer records below
DF2 <- read.table( text =
"case size
case1 120
case2 120
case3 121
case4 121
case5 121
case6 122
case7 122
", header=TRUE, as.is=TRUE )
# While you CAN use reshape to make long data out of wide data, that
# method for making long data will always presume you have the same number
# of records for each case. Combine your data directly into long form if
# that is how it is best represented.
# Below note the use of labels such as "Source" to organize the data
# Also note the use of "stringsAsFactors = FALSE" because concatenating
# factors is almost never a good idea... go read (again?) about what
# factors are if you don't understand why concatenating factors doesn't
# work well
DFL <- rbind( data.frame( Source = "DF1"
, size = DF1$size
, stringsAsFactors = FALSE
)
, data.frame( Source = "DF2"
, size = DF2$size
, stringsAsFactors = FALSE
)
)
# Your intent in making this graph is still a little opaque to me.. the
# breaks are causing logarithmic axis labels, but not all of the breaks
# show up
ggplot( data = DFL
, aes( x=size, fill=Source ) ) +
geom_histogram( binwidth = 500 ) + # might want "position='dodge`"?
scale_x_continuous( breaks = c( seq( 300, 800, by = 200 )
, seq( 1000, 15000, by = 1000 )
)
)
On Sat, 9 Jan 2016, maryam moazam wrote:
Dear Michael,
Thanks for your feedback. Actually, I would like to show (and compare) size
distribution of df1 and df2 in the single plot using ggplot2, something
like the attached picture. The command dosesn't lead me to this purpose.
However, I'm really new here, could you please help me more on this?
Thanks in advance,
Maryam
On Sat, Jan 9, 2016 at 5:38 PM, Michael Dewey <li...@dewey.myzen.co.uk>
wrote:
Dear Maryam
If you just need all the values of size would
c(df1$size, df2$size)
work?
On 08/01/2016 21:44, maryam moazam wrote:
Dear Sir / Madam,
I have just come to the amazing R software, so please be patient if my
question is basic for you. I have 2 text file (say 1.txt and 2.txt), each
file containing 2 columns and different row numbers, like below
case size
case1 120
case2 120
case3 121
case4 121
case5 121
case6 122
case7 122
case8 123
I would like to have a one plot for all text files, with x-axis shows the
size between 300-1200 with the interval of 200 (300,500,700,900,1200) and
size between 1201-1500 with the interval of 1000. For dataframes with the
equal row numbers, the following codes worked well,
df1 = data.frame("1.txt", header=T)
df2 = data.frame("2.txt", header=T)
*combining two dataframes with equal row number*
df = data.frame(df1$size,df2$size)
library(reshape)
melted <- melt(df)
ggplot(data=melted, aes(value))+aes(fill=variable)+ geom_histogram
(binwidth =500)+
+scale_x_continuous(breaks=c(seq(300,1000,by=200),seq(1001,15000,by=1000)))
but I couldn't reproduce the plot with these codes for dataframes with
different row number. I think the problem is* how to combine datafrmaes
with the different row number*, could you please help me out on this
issue?
Thank you in advance
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PLEASE do read the posting guide
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and provide commented, minimal, self-contained, reproducible code.
--
Michael
http://www.dewey.myzen.co.uk/home.html
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