I have a following type of csv
a,b,c
1,2,3
4,5,6
7,8,9
I would like to parse every column of this csv file into a list with out columns so the end result would be
myList = ["1","4","7","2","5","8","3","6","9"]
I have found many solutions for one column but i need to be flexible to be able to read every column of the file. I'm using an older version of python so i can't use any solutions with pandas library.
You could read the file fully and then zip the rows to transpose them, then chain the result to flatten the list. Standalone example (using a list of strings as input):
import csv,itertools
text="""a,b,c
1,2,3
4,5,6
7,8,9
""".splitlines()
myList = list(itertools.chain.from_iterable(zip(*csv.reader(text[1:]))))
print(myList)
result:
['1', '4', '7', '2', '5', '8', '3', '6', '9']
from a file it would read:
with open("test.csv") as f:
cr = csv.reader(f,separator=",") # comma is by default, but just in case...
next(cr) # skip title
myList = list(itertools.chain.from_iterable(zip(*cr)))
DictReader because the order of the values would depend on the order of the keys, which isn't what you want.
Simple approach:
d = """a,b,c
1,2,3
4,5,6
7,8,9
"""
cells = []
for line in d.split("\n"):
if line:
cells.append(line.strip().split(','))
print(cells)
for n in range(len(cells[0])):
for r in cells:
print(r[n])
Same iteration, but as generator:
def mix(t):
for n in range(len(t[0])):
for r in t:
yield r[n]
print( list( mix(cells) ) )
Using csv and chain to flatten the list
import csv
from itertools import chain
l = list(csv.reader(open('text.csv', 'r')))
mylist = map(list, zip(*l[1:])) # transpose list
list(chain.from_iterable(mylist)) # output ['1', '4', '7', '2', '5', '8', '3', '6', '9']
array