X-Git-Url: https://projects.mako.cc/source/gmail-maildir-counter/blobdiff_plain/f04f6e26f7c7fe4b079c847bc2dd563464305a35..221519b06e3d22b2c0fb4193f67b08a8d19822af:/README

diff --git a/README b/README
index 983163d..4e1d81f 100644
--- a/README
+++ b/README
@@ -3,13 +3,18 @@ Scripts to Count Messages from Google
 
 Author: Benjamin Mako Hill (mako@atdot.cc)
 License: GNU General Public License version 3 or any later version
-Home: http://projects.mako.cc/
+Code: http://projects.mako.cc/source/?p=gmail-maildir-counter
 
 I wrote this code in order to do the analysis I posted in this blog
 post:
 
 http://mako.cc/copyrighteous/google-has-most-of-my-email-because-it-has-all-of-yours
 
+If you want to send me patches or bugfixes, details on how to do that
+are here:
+
+http://projects.mako.cc/source/
+
 1. Parse your mailbox using the count_gmail.py script
 --------------------------------------------------------------
 
@@ -20,9 +25,27 @@ $ python count_gmail.py ~/incoming/mail/default > mail_metadata.tsv
 2. Parse the output using analysis.R
 --------------------------------------------------------------
 
-I run R interactively in Emacs/ESS but you might want to use RStudio
-if you are not familiar with Emacs. Alternatively, if you also output
-into mail_metadata.tsv, you can just run:
+If have not used R, you will to install R and three libraries I use in
+the script. 
+
+First, install R. In Debian and Ubuntu, the package is r-base. 
+
+You will then need to install three R libraries. The easiest way to do
+that is from within R. To start R, just invoke it from your shell:
+
+$ R
+
+Once R is running, you can install the packages by running these three
+commands from within the R interactive shell:
+
+> install.packages("data.table")
+> install.packages("ggplot2")
+> install.packages("reshape")
+
+Once youv'e done that, you can run the scripts.  I run R interactively
+in Emacs/ESS but you might want to use RStudio if you are not familiar
+with Emacs. Alternatively, if you also output into mail_metadata.tsv,
+you can just run:
 
 $ R --no-save < analysis.R
 
@@ -30,4 +53,4 @@ It will create the two PDFs files of graphs for you in the local directory.
 
 The I converted the PDFs into PNGs with imagemagick's mogrify:
 
-$ mogrify -format png *pdf
\ No newline at end of file
+$ mogrify -format png *pdf