This is my (abbreviated) text file (formatting might be lost in the post):
date close volume open high low
12:21 82.94 "14,748,136" 83.37 83.4 82.73
When I read the .txt file into Python it becomes a list which I then split. How would I take the list and reorder into column vectors? Any help would be much appreciated.
if you have a list of rows and you just want to change it to a list of columns you can simply do
transposed_list = zip(*original_list_of_rows)
but its not clear if you have a list of rows
Presumably, given that you have quotes around at least one of the values, it's possible for spaces to appear within a value. So, you can't just split().
You can parse it as a funky dialect of CSV, where the delimiter is a space, and initial whitespace is skipped:
with open('textfile') as f:
rows = list(csv.reader(f, delimiter=' ', skipinitialspace=True)
That will automatically handle the quotes for you and everything.
However, in at least some cases, columnar data like this can have values that aren't separated at all, like this:
date close volume open high low
12:21 82.94 "14,748,136" 83.37 83.4 82.73
12:22 93213.12"15,222,139" 93201.1493333.3390213.94
If so, then you can only parse it by slicing the lines at the appropriate column positions. If you're lucky, you can use the headers for this; otherwise, you'll need to specify them manually. I'll assume you're unlucky, so:
columns = 0, 7, 15, 31, 39, 47, None
def columnize(line):
return [line[columns[i]:columns[i+1]].rstrip() for i in range(len(columns)-1)]
with open('textfile') as f:
rows = map(columnize, f)
map calls, etc.) until you get to the end, I think Generator Tricks does a great job. And he's even got some parsing in there.[[x for i,x in enumerate(text.split()) if (i+j)%colNumber==0 ]
for j in range(colNumber)]
this requires you already know the column number and the text file is formmated as a table. for example:
text='''a b c
1 2 4
1 2 4
1 2 4
'''
colNumber=3
table=[[x for i,x in enumerate(text.split()) if (i+j)%colNumber==0 ]
for j in range(colNumber)]
print(table)
result:
[['a', '1', '1', '1'], ['c', '4', '4', '4'], ['b', '2', '2', '2']]
You can use pandas dataframes. (Hope this is a tab separated file)
import pandas as pd
import numpy as np
import csv
df = pd.read_csv('text.txt', sep='\t', header=None)
print df
Then you can rename the columns.
