making rows to column and saved in separate files - pandas

Question

I have 4 text file in a folder and each text file contain many rows of data as follows
cat a.txt
10.0000 0.0000 10.0000 0.0000
11.0000 0.0000 11.0000 0.0000
cat b.txt
5.1065 3.8423 2.6375 3.5098
4.7873 5.9304 1.9943 4.7599
cat c.txt
3.5257 3.9505 3.8323 4.3359
3.3414 4.0014 4.0383 4.4803
cat d.txt
1.8982 2.0342 1.9963 2.1575
1.8392 2.0504 2.0623 2.2037
I want to make each corresponding rows of the text file to column as
file001.txt
10.0000 5.1065 3.5257 1.8982
0.0000 3.8423 3.9505 2.0342
10.0000 2.6375 3.8323 1.9963
0.0000 3.5098 4.3359 2.1575
file002.txt
11.0000 4.7873 3.3414 1.8329
0.0000 5.9304 4.0014 2.0504
11.0000 1.9943 4.0383 2.0623
0.0000 4.7599 4.4803 2.2037
Anf finally I want to add this value 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000 to every line so the final output should be
file001.txt
10.0000 5.1065 3.5257 1.8982 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 3.8423 3.9505 2.0342 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
10.0000 2.6375 3.8323 1.9963 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 3.5098 4.3359 2.1575 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
file002.txt
11.0000 4.7873 3.3414 1.8329 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 5.9304 4.0014 2.0504 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
11.0000 1.9943 4.0383 2.0623 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 4.7599 4.4803 2.2037 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
Finally, I want to append some comments on the top of every created files
So for example file001.txt should be
#
# ascertain thin
# Metamorphs
# pch
# what is that
# 5-r
# Add the thing
# liop34
# liop36
# liop45
# liop34
# M(CM) N(M) O(S) P(cc) ab cd efgh ijkl mnopq rstuv
#
10.0000 5.1065 3.5257 1.8982 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 3.8423 3.9505 2.0342 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
10.0000 2.6375 3.8323 1.9963 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000
0.0000 3.5098 4.3359 2.1575 5.0000 6.0000 9.0000 0.0000 1.0000 1.0000

Answer 1

files = ["a.txt", "b.txt", "c.txt", "d.txt"]
# get number of columns per file, i.e., 4 in sample data
n_each = np.loadtxt(files[0]).shape[1]
# concatanate transposed data
arrays = np.concatenate([np.loadtxt(file).T for file in files])
# rows are in column now for easier reshaping; reshape and save
n_all = arrays.shape[1]
for n in range(n_all):
np.savetxt(f"file{str(n+1).zfill(3)}.txt",
arrays[:, n].reshape(n_each, len(files)).T,
fmt="%7.4f")
to add a fixed array of values right to the new arrays, you can perform horizontal stacking after tiling the new values n_each times:
# other things same as above
new_values = np.tile([5, 6, 9, 0, 1, 1], (n_each, 1))
for n in range(n_all):
np.savetxt(f"file{str(n+1).zfill(3)}.txt",
np.hstack((arrays[:, n].reshape(n_each, len(files)).T,
new_values)),
fmt="%7.4f")
to add comments, header and comments parameters of np.savetxt is useful. we pass the string to header and since it already contains "# " in it, we suppress extra "# " from np.savetxt by passing comments="":
comment = """\
#
# ascertain thin
# Metamorphs
# pch
# what is that
# 5-r
# Add the thing
# liop34
# liop36
# liop45
# liop34
# M(CM) N(M) O(S) P(cc) ab cd efgh ijkl mnopq rstuv
#"""
# rows are in column now for easier reshaping; reshape and save
n_all = arrays.shape[1]
new_values = np.tile([5, 6, 9, 0, 1, 1], (n_each, 1))
for n in range(n_all):
np.savetxt(f"file{str(n+1).zfill(3)}.txt",
np.hstack((arrays[:, n].reshape(n_each, len(files)).T,
new_values)),
fmt="%7.4f",
header=comment,
comments="")