adding values from a csv column and getting the mean. beginner help

[brian cleere]

I know the problem is with the for loop but don't know how to fix. Any help with explanation would be appreciated.

#!/bin/env python
import csv
import sys

if len(sys.argv) < 3:
print('Please specify a filename and column number: {} [csvfile] [column]'.format(sys.argv[0]))
sys.exit(1)

filename = sys.argv[1]
column = int(sys.argv[2])

for line in filename() , column ():
elements = line.strip().split(',')
values.append(int(elements[col]))

csum = sum(values)
cavg = sum(values)/len(values)
print("Sum of column %d: %f" % (col, csum))
print("Avg of column %d: %f" % (col, cavg))

 

[Tim Chase]

filename = sys.argv[1]
column = int(sys.argv[2])

for line in filename() , column ():
elements = line.strip().split(',')
values.append(int(elements[col]))

1) you need to open the file

2) you need to make use of the csv module on that file

3) you need to extract the column

Thus it would looks something like

column = int(sys.argv[2])
f = open(sys.argv[1], "rb")
r = csv.reader(f)
try:
for row in r:
values.append(int(row[column]))
finally:
f.close()

which can be obtusely written as

values = [int(row[column]) for row in csv.reader(open(sys.argv[1], "rb"))]

though the more expanded version allows you to do better error
handling (rows with insufficient columns, non-numeric/non-integer
values in the specified column, etc).

-tkc

 

[Mark Lawrence]

I know the problem is with the for loop but don't know how to fix. Any help with explanation would be appreciated.

#!/bin/env python
import csv

You never use the csv module.

import sys

if len(sys.argv) < 3:
print('Please specify a filename and column number: {} [csvfile] [column]'.format(sys.argv[0]))
sys.exit(1)

filename = sys.argv[1]
column = int(sys.argv[2])

for line in filename() , column ():

You're trying to loop around the filename and the column, you need to
open the file and loop around that.

elements = line.strip().split(',')

Please don't do this when you've got the csv module to do things for you.

values.append(int(elements[col]))

Where did values come from? Is it col or column, please make your mind up?

So let's stick things together. Something like.

values = []
with open(filename) as csvfile:
valuereader = csv.reader(csvfile)
for row in valuereader:
values.append(int(row[column]))

csum = sum(values)
cavg = sum(values)/len(values)
print("Sum of column %d: %f" % (col, csum))
print("Avg of column %d: %f" % (col, cavg))

I like consistency, new style formatting here, old style above, still if
it works for you.

 

[Mark Lawrence]

I know the problem is with the for loop but don't know how to fix. Any help with explanation would be appreciated.

Your problem is akin to debugging an empty file It's not so much a
matter of fixing what's not working as of starting at the very
beginning: How do you iterate over the content of a CSV file?

Now, you're almost there... partly. You have the split() call, which
will split on the comma, so if you go that route, all you need to do
is open the file, using the aptly-named builtin function "open".
You'll find docs on that if you do a quick search.

But you're actually part-way to the better solution. You're importing
the 'csv' module, which is exactly what you need here. All you need is
to read up on its docs:

http://docs.python.org/3/library/csv.html

I'm sure you can figure out the rest of your homework from there!

Now, with that out of the way, I'd like to just mention a couple of
other things.

print('Please specify a filename and column number: {} [csvfile] [column]'.format(sys.argv[0]))

Square brackets in a usage description often mean "optional". You may
want to be careful of that. There's no really good solution though.

There is, https://pypi.python.org/pypi/docopt/0.6.1

Once you've calculated the sum once, you can reuse that to calculate
the average. Can you see how?

And finally: You're using Google Groups to post, which means your
paragraphs are unwrapped, and - unless you fight very hard against a
stupidly buggy piece of software - your replies will be malformed and
ugly. Don't make yourself look bad; switch to a better newsreader, or
to the mailing list:

https://mail.python.org/mailman/listinfo/python-list

The content is the same, you just subscribe to the list and read and
write as email.

Ooh 'eck, we'll have the Popular Front for the Liberation of Google
Groups squad out in force again, vainly trying to defend the bug ridden
crap that they insist on using, and which I obviously won't mention.
Whoops!!!

Oh Lord, won't you buy me Mozilla Thunderbird ?
My friends all use GG, I think that's absurd.
Worked hard all my lifetime, no help from the nerds,
So Lord, won't you buy me Mozilla Thunderbird ?

With apologies to the late, great Janis Joplin.

 

[Chris Angelico]

There is, https://pypi.python.org/pypi/docopt/0.6.1

That appears to use <x> for a mandatory argument x, which is then
slightly ambiguous with shell redirection. But that's the best
notation I've ever seen for distinguishing mandatory args from fixed
keywords.

CrisA

 

[Mark Lawrence]

That appears to use <x> for a mandatory argument x, which is then
slightly ambiguous with shell redirection. But that's the best
notation I've ever seen for distinguishing mandatory args from fixed
keywords.

CrisA

I use the alternative X for a mandatory argument X.

 

[Chris Angelico]

I use the alternative X for a mandatory argument X.

Also common, but how do you specify a keyword, then? Say you have a
command with subcommands:

$0 foo x y
Move the foo to (x,y)
$0 bar x y z
Go to bar X, order a Y, and Z it [eg 'compress', 'gzip', 'drink']

How do you show that x/y/z are mandatory args, but foo/bar are
keywords to be typed exactly? In some formats italicized text can make
that distinction, but not in pure text.

ChrisA

 

[Mark Lawrence]

I use the alternative X for a mandatory argument X.

Also common, but how do you specify a keyword, then? Say you have a
command with subcommands:

$0 foo x y
Move the foo to (x,y)
$0 bar x y z
Go to bar X, order a Y, and Z it [eg 'compress', 'gzip', 'drink']

How do you show that x/y/z are mandatory args, but foo/bar are
keywords to be typed exactly? In some formats italicized text can make
that distinction, but not in pure text.

ChrisA

Haven't a clue off the top of my head so read all about it here
https://github.com/docopt/docopt

 

[Tim Chase]

Also common, but how do you specify a keyword, then? Say you have a
command with subcommands:

$0 foo x y
Move the foo to (x,y)
$0 bar x y z
Go to bar X, order a Y, and Z it [eg 'compress', 'gzip', 'drink']

How do you show that x/y/z are mandatory args, but foo/bar are
keywords to be typed exactly? In some formats italicized text can
make that distinction, but not in pure text.

I prefer {} notation:

$0 mv [--optional] {x} {y}
$0 bar [--mutually|--exclusive] {x} {y} {z}

-tkc

 

[Christopher Welborn]

On 11/12/2013 19:22, Chris Angelico wrote:
There is, https://pypi.python.org/pypi/docopt/0.6.1

+1 for docopt. It makes everything very clear. Just type out your usage
string, and then run docopt(usage_str) on it to get a dict of your args.
When I saw the video at http://docopt.org my jaw dropped. I couldn't
believe all of the arg parsing junk I had been writing for even the
smallest scripts. The other arg parsing libs make it easier than
manually doing it, but docopt is magic.

 

[M.F.]

I know the problem is with the for loop but don't know how to fix. Any help with explanation would be appreciated.

#!/bin/env python
import csv
import sys

if len(sys.argv) < 3:
print('Please specify a filename and column number: {} [csvfile] [column]'.format(sys.argv[0]))
sys.exit(1)

filename = sys.argv[1]
column = int(sys.argv[2])

for line in filename() , column ():
elements = line.strip().split(',')
values.append(int(elements[col]))

"filename" is a string, and "column" is an integer, the interpreter
should warn you that they are not callable
the above three lines could be changed to
==>
values = []
for line in open(filename):
elements = line.strip().split(',')
values.append(int(elements[column]))

or now that you have the "csv" module, you can use "csv.reader" to parse
the file:
==>
values = [ row[column] for row in csv.reader(open(filename, 'rb')) if
len(row) > column ]