I am very new to Python. I know that this has already been asked, and I apologise, but the difference in this new situation is that spaces between strings are not equal. I have a file, named coord, that contains the following space delimited strings:
   1  C       6.00    0.000000000    1.342650315    0.000000000
   2  C       6.00    0.000000000   -1.342650315    0.000000000
   3  C       6.00    2.325538562    2.685300630    0.000000000
   4  C       6.00    2.325538562   -2.685300630    0.000000000
   5  C       6.00    4.651077125    1.342650315    0.000000000
   6  C       6.00    4.651077125   -1.342650315    0.000000000
   7  C       6.00   -2.325538562    2.685300630    0.000000000
   8  C       6.00   -2.325538562   -2.685300630    0.000000000
   9  C       6.00   -4.651077125    1.342650315    0.000000000
  10  C       6.00   -4.651077125   -1.342650315    0.000000000
  11  H       1.00    2.325538562    4.733763602    0.000000000
  12  H       1.00    2.325538562   -4.733763602    0.000000000
  13  H       1.00   -2.325538562    4.733763602    0.000000000
  14  H       1.00   -2.325538562   -4.733763602    0.000000000
  15  H       1.00    6.425098097    2.366881801    0.000000000
  16  H       1.00    6.425098097   -2.366881801    0.000000000
  17  H       1.00   -6.425098097    2.366881801    0.000000000
  18  H       1.00   -6.425098097   -2.366881801    0.000000000
Please, note the spaces before the start of each string in the first column. So I have tried the following in order of converting it to csv:
with open('coord') as infile, open('coordv', 'w') as outfile:
    outfile.write(infile.read().replace("  ", ", "))
# Unneeded columns are deleted from the csv
input = open('coordv', 'rb')
output = open('coordcsvout', 'wb')
writer = csv.writer(output)
for row in csv.reader(input):
    if row:
        writer.writerow(row)
input.close()
output.close()
with open("coordcsvout","rb") as source:
    rdr= csv.reader( source )
    with open("coordbarray","wb") as result:
        wtr= csv.writer(result)
        for r in rdr:
            wtr.writerow( (r[5], r[6], r[7]) )
When I run the script, I get the following for the coordv in the very first part of the script, which is of course very wrong:
,  1, C, , ,  6.00, , 0.000000000, , 1.342650315, , 0.000000000
,  2, C, , ,  6.00, , 0.000000000,  -1.342650315, , 0.000000000
,  3, C, , ,  6.00, , 2.325538562, , 2.685300630, , 0.000000000
,  4, C, , ,  6.00, , 2.325538562,  -2.685300630, , 0.000000000
,  5, C, , ,  6.00, , 4.651077125, , 1.342650315, , 0.000000000
,  6, C, , ,  6.00, , 4.651077125,  -1.342650315, , 0.000000000
,  7, C, , ,  6.00,  -2.325538562, , 2.685300630, , 0.000000000
,  8, C, , ,  6.00,  -2.325538562,  -2.685300630, , 0.000000000
,  9, C, , ,  6.00,  -4.651077125, , 1.342650315, , 0.000000000
, 10, C, , ,  6.00,  -4.651077125,  -1.342650315, , 0.000000000
, 11, H, , ,  1.00, , 2.325538562, , 4.733763602, , 0.000000000
, 12, H, , ,  1.00, , 2.325538562,  -4.733763602, , 0.000000000
, 13, H, , ,  1.00,  -2.325538562, , 4.733763602, , 0.000000000
, 14, H, , ,  1.00,  -2.325538562,  -4.733763602, , 0.000000000
, 15, H, , ,  1.00, , 6.425098097, , 2.366881801, , 0.000000000
, 16, H, , ,  1.00, , 6.425098097,  -2.366881801, , 0.000000000
, 17, H, , ,  1.00,  -6.425098097, , 2.366881801, , 0.000000000
, 18, H, , ,  1.00,  -6.425098097,  -2.366881801, , 0.000000000
I have tried different possibilities in .replace without any success, and so far I haven't found any source of information on how I could do this. What would be the best way to get a comma-separated values from this coord file? What I'm interested is in using then the csv module in python to choose columns 4:6 and finally use numpy to import them as follows:
from numpy import genfromtxt
cocmatrix = genfromtxt('input', delimiter=',')
I'd be very glad if somebody could help me with this problem.
You can use csv:
import csv
with open(ur_infile) as fin, open(ur_outfile, 'w') as fout:
    o=csv.writer(fout)
    for line in fin:
        o.writerow(line.split())
                        You can use python pandas, I have written your data to data.csv:
import pandas as pd
>>> df = pd.read_csv('data.csv',sep='\s+',header=None)
>>> df
     0  1  2         3         4  5
0    1  C  6  0.000000  1.342650  0
1    2  C  6  0.000000 -1.342650  0
2    3  C  6  2.325539  2.685301  0
3    4  C  6  2.325539 -2.685301  0
4    5  C  6  4.651077  1.342650  0
5    6  C  6  4.651077 -1.342650  0
...
The great thing about this is to access the underlying numpy array you can use df.values:
>>> type(df.values)
<type 'numpy.ndarray'>
To save the data frame with comma delimiters:
>>> df.to_csv('data_out.csv',header=None)
Pandas is a great library for managing large amounts of data, as a bonus it works well with numpy. There is also a very good chance that this will be much faster then using the csv module.
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