I have a newbie question. I need help on separating a text file into columns and rows. Let's say I have a file like this:
1 2 3 4
2 3 4 5
and I want to put it into a 2d list called values = [[]]
i can get it to give me the rows ok and this code works ok:
values = map(int, line.split(','))
I just don't know how I can say the same thing but for the rows and the documentation doesn't make any sense
cheers
f = open(filename,'rt')
a = [[int(token) for token in line.split()] for line in f.readlines()[::2]]
In your sample file above, you have an empty line between each data row - I took this into account, but you can drop the ::2 subscript if you didn't mean to have this extra line in your data.
Edit: added conversion to int - you can use map as well, but mixing list comprehensions and map seems ugly to me.
readlines().
a = [[int(token) for token in line.split()] for line in file] (file being a valid file handle i.e. obtained from open)[int(token) for token in line.split()] takes each element of the list returned by line.split(), names it token and executes int() on it, thus forming another sequence, which contains all numbers in a line as integers. I could have chosen any other name.import csv
import itertools
values = []
with open('text.file') as file_object:
for line in csv.reader(file_object, delimiter=' '):
values.append(map(int, line))
print "rows:", values
print "columns"
for column in itertools.izip(*values):
print column
Output is:
rows: [[1, 2, 3, 4], [2, 3, 4, 5]]
columns:
(1, 2)
(2, 3)
(3, 4)
(4, 5)
Get the data into your program by some method. Here's one:
f = open(tetxfile, 'r')
buffer = f.read()
f.close()
Parse the buffer into a table (note: strip() is used to clear any trailing whitespace):
table = [map(int, row.split()) for row in buffer.strip().split("\n")]
>>> print table
[[1, 2, 3, 4], [2, 3, 4, 5]]
Maybe it's ordered pairs you want instead, then transpose the table:
transpose = zip(*table)
>>> print transpose
[(1, 2), (2, 3), (3, 4), (4, 5)]
You could try to use the CSV-module. You can specify custom delimiters, so it might work.
If columns are separated by blanks
import re
A,B,C,D = [],[],[],[]
pat = re.compile('([^ ]+)\s+([^ ]+)\s+([^ ]+)\s+([^ ]+)')
with open('try.txt') as f:
for line in f:
a,b,c,d = pat.match(line.strip()).groups()
A.append(int(a));B.append(int(b));C.append(int(c));D.append(int(d))
or with csv module
EDIT
A,B,C,D = [],[],[],[]
with open('try.txt') as f:
for line in f:
a,b,c,d = line.split()
A.append(int(a));B.append(int(b));C.append(int(c));D.append(int(d))
But if there are more than one blank between elements of data, this code will fail
EDIT 2
Because the solution with regex has been qualified of extremely hard to understand, it can be cleared as follows:
import re
A,B,C,D = [],[],[],[]
pat = re.compile('\s+')
with open('try.txt') as f:
for line in f:
a,b,c,d = pat.split(line.strip())
A.append(int(a));B.append(int(b));C.append(int(c));D.append(int(d))
re.compile('\s+') works only because \s is not a recognized escape sequence. Therefore, it is official recommendation to always use raw strings when specifying regexes.