As mentioned by others, you can do this using pandas transpose() method.
>>> import pandas
>>> file_obj = '''25 05 38 26 53 04
... 07 45 50 33 19 34
... 55 25 21 30 09 39
... 26 11 30 12 13 41
... 32 23 44 11 50 39
... 45 30 07 44 55 54
... 21 10 35 46 48 27
... 52 41 05 53 11 50
... 40 38 17 43 10 54
... 45 27 29 12 39 31
... 24 42 38 02 18 09
... 13 43 28 06 53 30
... 45 47 29 30 53 13
... 38 45 28 48 47 36
... 25 34 18 06 07 55'''.split('\n')
>>> data = []
>>> for row in file_obj:
... data.append(row.split())
...
>>> data
[['25', '05', '38', '26', '53', '04'], ['07', '45', '50', '33', '19', '34'], ['55', '25', '21', '30', '09', '39'], ['26', '11', '30', '12', '13', '41'], ['32', '23', '44', '11', '50', '39'], ['45', '30', '07', '44', '55', '54'], ['21', '10', '35', '46', '48', '27'], ['52', '41', '05', '53', '11', '50'], ['40', '38', '17', '43', '10', '54'], ['45', '27', '29', '12', '39', '31'], ['24', '42', '38', '02', '18', '09'], ['13', '43', '28', '06', '53', '30'], ['45', '47', '29', '30', '53', '13'], ['38', '45', '28', '48', '47', '36'], ['25', '34', '18', '06', '07', '55']]
>>> df = pandas.DataFrame(data)
>>> df
0 1 2 3 4 5
0 25 05 38 26 53 04
1 07 45 50 33 19 34
2 55 25 21 30 09 39
3 26 11 30 12 13 41
4 32 23 44 11 50 39
5 45 30 07 44 55 54
6 21 10 35 46 48 27
7 52 41 05 53 11 50
8 40 38 17 43 10 54
9 45 27 29 12 39 31
10 24 42 38 02 18 09
11 13 43 28 06 53 30
12 45 47 29 30 53 13
13 38 45 28 48 47 36
14 25 34 18 06 07 55
>>> rotated = df.transpose()
>>> rotated
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0 25 07 55 26 32 45 21 52 40 45 24 13 45 38 25
1 05 45 25 11 23 30 10 41 38 27 42 43 47 45 34
2 38 50 21 30 44 07 35 05 17 29 38 28 29 28 18
3 26 33 30 12 11 44 46 53 43 12 02 06 30 48 06
4 53 19 09 13 50 55 48 11 10 39 18 53 53 47 07
5 04 34 39 41 39 54 27 50 54 31 09 30 13 36 55
If you'd rather do it manually, that's also fairly easy (pandas DataFrame added to the end, to show they're the same).
>>> file_obj = '''25 05 38 26 53 04
... 07 45 50 33 19 34
... 55 25 21 30 09 39
... 26 11 30 12 13 41
... 32 23 44 11 50 39
... 45 30 07 44 55 54
... 21 10 35 46 48 27
... 52 41 05 53 11 50
... 40 38 17 43 10 54
... 45 27 29 12 39 31
... 24 42 38 02 18 09
... 13 43 28 06 53 30
... 45 47 29 30 53 13
... 38 45 28 48 47 36
... 25 34 18 06 07 55'''.split('\n')
>>> columns = []
>>> for row in file_obj:
... values = row.split()
... for index, val in enumerate(values):
... if index >= len(columns):
... columns.append([])
... columns[index].append(val)
...
>>> columns
[['25', '07', '55', '26', '32', '45', '21', '52', '40', '45', '24', '13', '45', '38', '25'], ['05', '45', '25', '11', '23', '30', '10', '41', '38', '27', '42', '43', '47', '45', '34'], ['38', '50', '21', '30', '44', '07', '35', '05', '17', '29', '38', '28', '29', '28', '18'], ['26', '33', '30', '12', '11', '44', '46', '53', '43', '12', '02', '06', '30', '48', '06'], ['53', '19', '09', '13', '50', '55', '48', '11', '10', '39', '18', '53', '53', '47', '07'], ['04', '34', '39', '41', '39', '54', '27', '50', '54', '31', '09', '30', '13', '36', '55']]
>>> pandas.DataFrame(columns)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0 25 07 55 26 32 45 21 52 40 45 24 13 45 38 25
1 05 45 25 11 23 30 10 41 38 27 42 43 47 45 34
2 38 50 21 30 44 07 35 05 17 29 38 28 29 28 18
3 26 33 30 12 11 44 46 53 43 12 02 06 30 48 06
4 53 19 09 13 50 55 48 11 10 39 18 53 53 47 07
5 04 34 39 41 39 54 27 50 54 31 09 30 13 36 55