Reading data into numpy array from text file

I have a file with some metadata, and then some actual data consisting of 2 columns with headings. Do I need to separate the two types of data before using genfromtxt in numpy? Or can I somehow split the data maybe? What about placing the file pointer to the end of the line just above the headers, and then trying genfromtxt from there? Thanks The format of the file is shown below:

 &SRS
<MetaDataAtStart>
multiple=True
Wavelength (Angstrom)=0.97587
mode=assessment
background=True
issid=py11n2g
noisy=True
</MetaDataAtStart>
&END
Two Theta(deg)  Counts(sec^-1)
10.0    41.0
10.1    39.0
10.2    38.0
10.3    38.0
10.4    41.0
10.5    42.0
10.6    38.0
10.7    44.0
10.8    42.0
10.9    39.0
11.0    37.0
11.1    37.0
11.2    45.0
11.3    36.0
11.4    37.0
11.5    37.0
11.6    40.0
11.7    44.0
11.8    45.0
11.9    46.0
12.0    44.0
12.1    40.0
12.2    41.0
12.3    39.0
12.4    41.0

Answers


If you don't want the first n rows, try (if there is no missing data):

data = numpy.loadtxt(yourFileName,skiprows=n)

or (if there are missing data):

data = numpy.genfromtxt(yourFileName,skiprows=n)    

If you then want to parse the header information, you can go back and open the file parse the header, for example:

fh = open(yourFileName,'r')
for i,line in enumerate(fh):
    if i is n: break
    do_other_stuff_to_header(line)
fh.close()

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