Talent

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One good option for plotting is to use PYTHON's matplotlib. Below a sample script you can modify. This one graphs contents of a file called liquid.dat

from numpy import *
from pylab import *
from matplotlib import rc, rcParams
import matplotlib.units as units
import matplotlib.ticker as ticker
import sys
import os
# set tickers etc
rc('text',usetex=True)
rc('font',**{'family':'serif','serif':['Binding energies']})
title(r'{\bf Binding energies}', fontsize=20)     
# read in data from file
BEdata = loadtxt("liquid.dat")
l = len(BEdata[:,0])
x = BEdata[:,2]
y = BEdata[:,3]
z = BEdata[:,4]
axis([0,270,-1, 10.0])
xlabel(r'$A$',fontsize=20)
ylabel(r'$\mathrm{BE}$ [MeV]',fontsize=20)
plot(x, y ,'ro', x, z, 'bo', markersize=7)
# Save the figure in a separate file
savefig('beexpliquid.pdf', format='pdf')
# Draw the plot to screen
show()

The data file for this example looks like this: 1 1 2 1.112300 0.991998 0.120302 1 2 3 2.827267 0.368785 2.458482 1 3 4 1.720450 -1.640617 3.361067 1 4 5 1.336360 -3.337299 4.673659 1 5 6 0.961633 -4.647357 5.608990 1 6 7 1.111686 -5.656402 6.768088 2 1 3 2.572667 -0.126275 2.698941 2 2 4 7.073925 3.822039 3.251886 2 3 5 5.512140 3.836172 1.675968 2 4 6 4.878400 2.889512 1.988888 2 5 7 4.123914 1.759144 2.364770 2 6 8 3.924525 0.671628 3.252897 2 7 9 3.477355 -0.310644 3.787999 2 8 10 3.033860 -1.178539 4.212399 3 1 4 1.153750 -2.540201 3.693951 3 2 5 5.266140 3.418622 1.847518 3 3 6 5.332333 5.139848 0.192485 3 4 7 5.606442 5.280293 0.326149 3 5 8 5.159712 4.798504 0.361208 3 6 9 5.037767 4.081375 0.956392 3 7 10 4.531350 3.295756 1.235594 3 8 11 4.155364 2.515579 1.639785 3 9 12 3.799083 1.772972 2.026111 3 10 13 3.403000 1.080470 2.322530 4 2 6 4.487250 2.103653 2.383597