I'm trying to add a feature to the code below but seem to be messing up somewhere.
The following code basically repeats the first "z" table columns for each of the following speakers (like a excel transposition). For these columns after "z" are dates and just want a date column.
The problem is that the python script generates the values correctly but need it insert the column talking about what that date, repeat this information to all the values that date.
Python script:
from itertools chain from import
f = open ("C:\\Test.CSV", "r")
sep = ""
M = []
M = [M + [s.strip () for s in line.split (sep)] for line in f.readlines ()]
f.close ()
i = 0 # title
w = 4 # cols in title
r = 1 # body
z = 4 # fields fix
result = [M [i] [w] + ["date"] + ["Value"]] + list (chain (* [[x [: z] + [y] for y in x [z + 1: ]] for x in M [A:]]))
f = open ("C:\out.csv", 'w')
f.writelines ("\ n" .join ("". join (s) for s in result) + "\ 0")
f.close ()
Something (input):
[[X; y; date1; date2; date3]
[01; 02; 03; 04; 05]
[06; 07; 08; 09; 10]
[11; 12; 13, 14 15]]
The current script does this correctly (output now):
[[X; y; date1]
[01; 02; 03]
[01; 02; 04]
[01; 02; 05]
[06; 07; 08]
[06; 07; 09]
[06; 07; 10]
[11; 12; 13]
[11; 12; 14]
[11; 12; 15]]
I take the output is this (desired output):
[[X; y; date; value; ]
[01; 02; date1; 03]
[01; 02; date2; 04]
[01; 02; date3; 05]
[06; 07; date1; 08]
[06; 07; date2; 09]
[06; 07; date3; 10]
[11; 12; date1; 13]
[11; 12; date2; 14]
[11; 12; date3; 15]]
Has anyone done something like that?
Any reason you can't just use csv?
import csv
f = open("iter.csv", "r")
g = open("out.csv", "w", newline="")
transpose_columns = ['date1', 'date2', 'date3']
target_columns = ['date', 'value']
reader = csv.DictReader(f)
writer = csv.DictWriter(g, fieldnames=[a for a in reader.fieldnames
if a not in transpose_columns] + target_columns,
extrasaction='ignore')
writer.writeheader()
for row in reader:
for col in transpose_columns:
row[target_columns[0]] = col
row[target_columns[1]] = row[col]
writer.writerow(row)
f.close()
g.close()