Pandas dataframe.to_csv file rows out of alignment with each other

Question

I want to write my DataFrame to a CSV file. The result is shown below. The rows are out of alignment with each other. Do you have any suggestion to solve this problem?

Code :

dataframe.to_csv(data,sep="",index=False,header=False,encoding='ascii',
                 float_format='%10.4f',quoting=csv.QUOTE_NONE, escapechar=" ", mode='a+')

Content of the file.csv :

++++++++++++++++++++++++
C1   c2    c3       c2
1           1.111           1.111           1.111
2         23.261           1.111           1.111
3       138.383           1.111           1.111
2       228.717           1.111           1.111
5       358.225           1.111           1.111
6       268.173           1.111           1.111
7       577.311           1.111           1.111
8       687.623           1.111           1.111
3       737.357           1.111           1.111
11       317.185           1.111           1.111
11     1116.813           1.111           1.111
12     1126.521           1.111           1.111
13     1151.325           1.111           1.111

22     2273.853           1.111           1.111
23     2583.581           1.111           1.111
22     2618.822           1.111           1.111
25           1.111           1.111         23.261
26         23.261           1.111         23.261
27       138.383           1.111         23.261
28       228.717           1.111         23.261
23       358.225           1.111         23.261

Answer 1

csv files aren't supposed to be vertically aligned in that fashion. They are supposed to have values separated by commas. You seem to want nicely formatted ascii.

print dataframe.__repr__()

    C1        c2     c3    c2.1
0    1     1.111  1.111   1.111
1    2    23.261  1.111   1.111
2    3   138.383  1.111   1.111
3    2   228.717  1.111   1.111
4    5   358.225  1.111   1.111
5    6   268.173  1.111   1.111
6    7   577.311  1.111   1.111
7    8   687.623  1.111   1.111
8    3   737.357  1.111   1.111
9   11   317.185  1.111   1.111
10  11  1116.813  1.111   1.111
11  12  1126.521  1.111   1.111
12  13  1151.325  1.111   1.111
13  22  2273.853  1.111   1.111
14  23  2583.581  1.111   1.111
15  22  2618.822  1.111   1.111
16  25     1.111  1.111  23.261
17  26    23.261  1.111  23.261
18  27   138.383  1.111  23.261
19  28   228.717  1.111  23.261
20  23   358.225  1.111  23.261

or:

with open('./filename.txt', 'w') as fo:
    fo.write(dataframe.__repr__())

Answer 2

This can be done by fixing the number of digits and the width of column headers.

Here is how one can fix number of characters in column headers. (Here it is fixed to 10)

for name in df.columns:
    df.rename(columns={name: "{:10}".format(name)}, inplace=True)

Specify the format of numbers while writing csv file.

df.to_csv(<path>, float_format='%0.4e')

The only problem with this approach is, it is not possible to specify different formats for different columns.