CSV methodology

kjs bfb at riseup.net
Sun Sep 14 04:51:25 CEST 2014



jetrn at newsguy.com wrote:
> 
> Hello.  Back in the '80s, I wrote a fractal generator, which, over the years,
> I've modified/etc to run under Windows.  I've been an Assembly Language
> programmer for decades.  Recently, I decided to learn a new language,
> and decided on Python, and I just love it, and the various IDEs.
> 
> 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:
> 
> -----------------------------------------------
> 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)
> -----------------------------------------------


The csv.reader(f) object creates an iterable that will create lists from
lines in f. The list will have values at indexes based on the commas in
the file. EX:

my_header_1, my_header_2
111, 0001
101, 1010
100, 1001

The csv.reader will lazily make lists like ['my_header_1',
'my_header_2'], ['111', '0001'], ... and so forth.

Your program above will take the length of those lists, and assign that
value to x. For every line in the file, f will get rewritten with a new
value, the length of list which is derived from the number of commas in
the csv.

Also note that the csv.reader speaks many dialects, and can do similar
work on files with different quote characters and delimiters.

Generally, I prefer to read in csv files with the standard readline()
method of open files. I do like to use csv.DictWriter, which helps me to
keep my csv output tabular.

-Kevin

> 
> 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.
> 
> Advice?
> 
> Jeff
> 
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