On 13Sep2014 21:34, je...@newsguy.com <je...@newsguy.com> wrote:
Hello. Back in the '80s, I wrote a fractal generator, [...]
Anyway, something I thought would be interesting, would be to export
some data from my fractal program (I call it MXP), and write something
in Python and its various scientific data analysis and plotting modules,
and... well, see what's in there.
An example of the data:
1.850358651774470E-0002
32
22
27
... (this format repeats)
So, I wrote a procedure in MXP which converts "the data" and exports
a csv file. So far, here's what I've started with:
Normally a CSV file will have multiple values per row. Echoing Terry, what
shape did you intend your CSV data to be? i.e. what values appear on a row?
import csv
fname = 'E:/Users/jayte/Documents/Python Scripts/XportTestBlock.csv'
f = open(fname)
reader = csv.reader(f)
for flt in reader:
x = len(flt)
file.close(f)
This will get me an addressable array, as:
flt[0], flt[1], flt[350], etc... from which values can be assigned to
other variables, converted...
My question: Is there a better way? Do I need to learn more about
how csv file are organized? Perhaps I know far too little of Python
to be attempting something like this, just yet.
If you have a nice regular CSV file, with say 3 values per row, you can go:
reader = csv.reader(f)
for row in reader:
a, b, c - row
and proceed with a, b and c directly from there. But of course, that requires
your export format to be usable that way.
Cheers,
Cameron Simpson <c...@zip.com.au>
For a good prime, call: 391581 * 2^216193 -1
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