How to add a "column" back to txt file after creating the column with pandas?

So I have a .LAS file (it works practically as txt file) and I converted it to a dataframe. Later I created a new column with some important information on the dataframe. Is there a way to rewrite the LAS file similar to the original one, but now with the new column?

Here is how my LAS file was:

Text 1
Text 2
Text 3
Text 4
~A Stats1 Stats2 Stats3
     1       2     3
     6       6     7
     8       9     3

So I managed to convert the file to a DataFrame the way I wanted (without the header and '~A'):

with open(r'C:...filename.las') as f:
    for l in f:
        if l.startswith('~A'):
            stats= l.split()[1:]
            break
    data = pd.read_csv(f, names=stats, sep='~A', engine='python')

data

Stats1 Stats2 Stats3 Numbers
  1       2      3      1
  6       6      7      2
  8       9      3      3

Now, imagine that I created a new column data['Numbers'] with numbers(1,2,3) and if I managed to rewrite this back to my LAS file, it should be like:

```
Text 1
Text 2
Text 3
Text 4
~A Stats1 Stats2 Stats3 Numbers
     1       2     3       1
     6       6     7       2
     8       9     3       3
```

Anyone knows how can I do that?

if I just use: np.savetxt('filename_edited.las', data, fmt="%s") ...I manage to get the new LAS file with the data I wanted, but without the header I had on the original file.

Thanks!

Solution

You need to save the header when reading the file, so you can write it back. Otherwise it's lost.

To write the dataframe, you can use pandas.DataFrame.to_csv after you have written back the header text.

with open('data.txt') as f:
    file_header = []
    for l in f:
        if l.startswith('~A'):
            stats= l.split()[1:]
            break
        else:
            file_header.append(l)

    data = pd.read_csv(f, names=stats, sep='\s+', engine='python')

#manipulate the dataframe to add a column or whatever
data['numbers'] = [1, 2, 3]

with open('data2.txt', 'w') as wf:
    data_str = data.to_csv(None)
    for l in file_header:
        wf.write(l)
    wf.write('~A')
    wf.write(data_str)

And data2.txt will look like:

Text 1
Text 2
Text 3
Text 4
~A,Stats1,Stats2,Stats3,numbers
0,1,2,3,1
1,6,6,7,2
2,8,9,3,3

to_csv use a comma separator by default, but you can use the sep argument to specify a different one. Must be a string of length 1.