column removal in a several consecutive text files of the same directory, python
Question
I'm looking to manipulate a text files and remove all irrelevant columns after removing irrelevant rows(already done),of course leaving only the fifth and sixth column , while being able to run it an a whole directory of files at once, instead of going one file at a time
i have written the first part in which i remove the irrelevant rows
this a sample of the file after row removal
ABCDE 1 * 2003-04-27T20:05:00.000 +016.477000 -31.640000 ABCDE_00002_ABC 1496 341.25 1 979477.00 1 -10.31 1 22.62 1
ABCDE 2 * 2003-04-27T20:05:20.000 +016.477000 -31.640000 ABCDE_00002_ABC 1496 341.40 1 979477.00 1 -10.93 1 22.56 1
ABCDE 3 * 2003-04-27T20:05:40.000 +016.477000 -31.640000 ABCDE_00002_ABC 1496 341.48 1 979477.44 1 -10.87 1 23.00 1
ABCDE 4 * 2003-04-27T20:06:00.000 +016.477000 -31.640000 ABCDE_00002_ABC 1496 341.80 1 979478.88 1 -9.76 1 24.37 1
ABCDE 5 * 2003-04-27T20:06:20.000 +016.476000 -31.640000 ABCDE_00002_ABC 1496 341.80 1 979478.44 1 -10.20 1 23.87 1
ABCDE 6 * 2003-04-27T20:06:40.000 +016.476000 -31.640000 ABCDE_00002_ABC 1496 341.53 1 979475.19 1 -12.79 1 20.62 1
ABCDE 7 * 2003-04-27T20:07:00.000 +016.476000 -31.640000 ABCDE_00002_ABC 1496 341.60 1 979472.69 1 -14.93 1 18.06 1
ABCDE 8 * 2003-04-27T20:07:20.000 +016.476000 -31.640000 ABCDE_00002_ABC 1496 341.80 1 979473.38 1 -14.93 1 18.75 1
ABCDE 9 * 2003-04-27T20:07:40.000 +016.475000 -31.640000 ABCDE_00002_ABC 1496 341.80 1 979475.56 1 -13.25 1 20.87 1
ABCDE 10 * 2003-04-27T20:08:00.000 +016.475000 -31.640000 ABCDE_00002_ABC 1496 341.90 1 979476.56 1 -12.74 1 21.87 1
ABCDE 11 * 2003-04-27T20:08:20.000 +016.475000 -31.640000 ABCDE_00002_ABC 1496 341.90 1 979477.44 1 -12.63 1 22.69 1
ABCDE 12 * 2003-04-27T20:08:40.000 +016.475000 -31.640000 ABCDE_00002_ABC 1496 341.95 1 979476.69 1 -13.31 1 21.94 1
ABCDE 13 * 2003-04-27T20:09:00.000 +016.475000 -31.640000 ABCDE_00002_ABC 1496 342.10 1 979476.31 1 -13.97 1 21.50 1
ABCDE 14 * 2003-04-27T20:09:20.000 +016.474000 -31.640000 ABCDE_00002_ABC 1496 342.23 1 979477.19 1 -13.69 1 22.37 1
ABCDE 15 * 2003-04-27T20:09:40.000 +016.474000 -31.640000 ABCDE_00002_ABC 1496 342.44 1 979478.25 1 -13.08 1 23.37 1
ABCDE 16 * 2003-04-27T20:10:00.000 +016.474000 -31.640000 ABCDE_00002_ABC 1496 342.60 1 979479.56 1 -12.53 1 24.69 1
ABCDE 17 * 2003-04-27T20:10:20.000 +016.474000 -31.640000 ABCDE_00002_ABC 1496 342.75 1 979480.94 1 -12.58 1 26.00 1
ABCDE 18 * 2003-04-27T20:10:40.000 +016.473000 -31.640000 ABCDE_00002_ABC 1496 342.78 1 979479.81 1 -14.59 1 24.87 1
ABCDE 19 * 2003-04-27T20:11:00.000 +016.473000 -31.640000 ABCDE_00002_ABC 1496 342.77 1 979478.12 1 -16.83 1 23.12 1
ABCDE 20 * 2003-04-27T20:11:20.000 +016.473000 -31.640000 ABCDE_00002_ABC 1496 342.90 1 979477.00 1 -18.18 1 22.00 1
ABCDE 21 * 2003-04-27T20:11:40.000 +016.472000 -31.640000 ABCDE_00002_ABC 1496 342.78 1 979476.50 1 -19.35 1 21.50 1
ABCDE 22 * 2003-04-27T20:12:00.000 +016.472000 -31.640000 ABCDE_00002_ABC 1496 342.75 1 979477.75 1 -18.46 1 22.69 1
ABCDE 23 * 2003-04-27T20:12:20.000 +016.472000 -31.640000 ABCDE_00002_ABC 1496 342.10 1 979478.81 1 -18.07 1 23.75 1
ABCDE 24 * 2003-04-27T20:12:40.000 +016.472000 -31.640000 ABCDE_00002_ABC 1496 342.46 1 979478.88 1 -18.85 1 23.75 1
ABCDE 25 * 2003-04-27T20:13:00.000 +016.471000 -31.640000 ABCDE_00002_ABC 1496 342.78 1 979478.81 1 -19.52 1 23.69 1
ABCDE 26 * 2003-04-27T20:13:20.000 +016.471000 -31.640000 ABCDE_00002_ABC 1496 343.33 1 979478.00 1 -20.02 1 22.81 1
ABCDE 27 * 2003-04-27T20:13:40.000 +016.471000 -31.650000 ABCDE_00002_ABC 1496 343.63 1 979476.94 1 -20.75 1 21.75 1
ABCDE 28 * 2003-04-27T20:14:00.000 +016.470000 -31.650000 ABCDE_00002_ABC 1496 344.42 1 979476.19 1 -21.20 1 20.94 1
ABCDE 29 * 2003-04-27T20:14:20.000 +016.470000 -31.650000 ABCDE_00002_ABC 1496 343.20 1 979477.25 1 -20.52 1 22.00 1
ABCDE 30 * 2003-04-27T20:14:40.000 +016.469000 -31.650000 ABCDE_00002_ABC 1496 343.93 1 979479.81 1 -18.85 1 24.56 1
ABCDE 31 * 2003-04-27T20:15:00.000 +016.469000 -31.650000 ABCDE_00002_ABC 1496 344.27 1 979481.06 1 -18.78 1 25.75 1
ABCDE 32 * 2003-04-27T20:15:20.000 +016.469000 -31.650000 ABCDE_00002_ABC 1496 344.10 1 979481.62 1 -19.68 1 26.31 1
this part removed the irrelevant rows
target_file = 'directory/F11.txt copy.txt'
after_lines = 'Anew.txt'
after_columns = 'Bnew.txt'
infile = open(target_file,'r').readlines()
with open(after_lines, 'w') as outfile:
for index, line in enumerate(infile):
if index >= 8:
outfile.write(line)
need to remove columns remaining with only the fifth and sixth column left
end result should look like this
+016.477000 -31.640000
+016.477000 -31.640000
+016.477000 -31.640000
+016.477000 -31.640000
+016.476000 -31.640000
+016.476000 -31.640000
+016.476000 -31.640000
+016.476000 -31.640000
+016.475000 -31.640000
+016.475000 -31.640000
+016.475000 -31.640000
+016.475000 -31.640000
+016.475000 -31.640000
+016.474000 -31.640000
+016.474000 -31.640000
+016.474000 -31.640000
+016.474000 -31.640000
+016.473000 -31.640000
+016.473000 -31.640000
+016.473000 -31.640000
+016.472000 -31.640000
+016.472000 -31.640000
+016.472000 -31.640000
+016.472000 -31.640000
+016.471000 -31.640000
+016.471000 -31.640000
+016.471000 -31.650000
+016.470000 -31.650000
+016.470000 -31.650000
+016.469000 -31.650000
+016.469000 -31.650000
+016.469000 -31.650000
1 answers
solution1
0 ACCPTED 2019-08-06 12:41:58
Read one line, extract the data you need from it, write it to the other file. Rinse, repeat:
with open("input.txt") as In, open("output.txt", "w") as Out:
for line in In:
values = line.split()
Out.write(f"{values[4]} {values[5]}\n")
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