MiB Xvnc
13.7 MiB + 515.5 KiB = 14.2 MiB yum-updatesd
16.3 MiB + 1.6 MiB = 17.9 MiB nautilus
20.8 MiB + 1.4 MiB = 22.2 MiB puplet
1.5 GiB + 438.0 KiB = 1.5 GiB java
-
1.7 GiB
==
: R mailing list
Date: 08/30/2013 07:14 PM
Subject: Re: [R] Memory usage bar plot
Here is how to parse the data and put it into groups. Not sure what
the 'timing' of each group is since not time information was given.
Also not sure is there is an 'MiB' qualifier o
## Here is a plot. The input was parsed with Jim Holtman's code.
## The panel.dumbell is something I devised to show differences.
## Rich
input <- readLines(textConnection("
Private + Shared = RAM used Program
96.0 KiB + 11.5 KiB = 107.5 KiB uuidd
108.0 KiB + 12.5 KiB = 12
Hi
From: mohan.radhakrish...@polarisft.com
[mailto:mohan.radhakrish...@polarisft.com]
Sent: Friday, August 30, 2013 3:16 PM
To: PIKAL Petr
Cc: r-help@r-project.org
Subject: RE: [R] Memory usage bar plot
Hello,
This memory usage should be graphed with time. Are there
examples of
be better.
Petr
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of mohan.radhakrish...@polarisft.com
> Sent: Friday, August 30, 2013 1:25 PM
> To: r-help@r-project.org
> Subject: [R] Memory usage bar plot
>
.0 KiB gpm
#14 162.5 KiB pam_timestamp_check
A.K.
- Original Message -
From: jim holtman
To: mohan.radhakrish...@polarisft.com
Cc: R mailing list
Sent: Friday, August 30, 2013 9:44 AM
Subject: Re: [R] Memory usage bar plot
Here is how to parse the data and put it into groups.
Here is how to parse the data and put it into groups. Not sure what
the 'timing' of each group is since not time information was given.
Also not sure is there is an 'MiB' qualifier on the data, but you have
the matrix of data which is easy to do with as you want.
> input <- readLines(textConnect
ect.org"
Date: 08/30/2013 05:33 PM
Subject: RE: [R] Memory usage bar plot
Hi
For reading data into R you shall look to read.table and similar.
For plotting ggplot could handle it. However I wonder if 100 times 50 bars
is the way how to present your data. You shall think over
Hi,
I haven't tried the code yet. Is there a way to parse this data
using R and create bar plots so that each program's 'RAM used' figures are
grouped together.
So 'uuidd' bars will be together. The data will have about 50 sets. So if
there are 100 processes each will have about 50 bar
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