Colin Ross wrote: > Good afternoon, > > I have a .dat file that is 214 rows by 65 columns that I would like to > read into python and plot the 1st column versus all other columns. > > My code: > > ######################################################################### > > import numpy as np > import scipy > import pylab as pl > import matplotlib > from matplotlib.ticker import ScalarFormatter, FormatStrFormatter > import sys > > # Load in text from .dat file > > sed = np.loadtxt('spectra.dat', unpack = True)
for flux in sed: pl.plot(wavelength, flux) > pl.xscale('log') > > pl.show() > > ######################################################################### > > This is fine if I want to write out a separate line for each of the 65 > columns, but I would like to simplify the code by looping over the data. > Can someone please help me formatting the loop correctly? To understand why the above works (assuming it does) consider that for many data types for item in data: ... # use item is equivalent to for index in range(len(data)): item = data[index] ... # use item Unrolling the above for len(data) == 3 gives: item = data[0] ... # use first item item = data[1] ... # use second item item = data[2] ... # use third item _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor