I am not familiar with how to export the list to the csv in python. Here is code for one list:
import csv
X = ([1,2,3],[7,8,9])
Y = ([4,5,6],[3,4,5])
for x in range(0,2,1):
csvfile = "C:/Temp/aaa.csv"
with open(csvfile, "w") as output:
writer = csv.writer(output, lineterminator='\n')
for val in x[0]:
writer.writerow([val])
And I want to the result:
Then how to modify the code(the main problem is how to change the column?)
To output multiple columns you can use zip() like:
import csv
x0 = [1, 2, 3]
y0 = [4, 5, 6]
x2 = [7, 8, 9]
y2 = [3, 4, 5]
csvfile = "aaa.csv"
with open(csvfile, "w") as output:
writer = csv.writer(output, lineterminator='\n')
writer.writerow(['x=0', None, None, 'x=2'])
writer.writerow(['x', 'y', None, 'x', 'y'])
for val in zip(x0, y0, [None] * len(x0), x2, y2):
writer.writerow(val)
x=0,,,x=2
x,y,,x,y
1,4,,7,3
2,5,,8,4
3,6,,9,5
x0 and x2. This is extremely bad practice if you want to iterate over them as a group. How about using a dict so that you can properly iterate? Other than that does this answer answer the question you asked?You could try:
with open('file.csv') as fin:
reader = csv.reader(fin)
[fout.write(r[0],r[1]) for r in reader]
If you need further help, leave a comment.
When dealing with csv files you should really just use Pandas. Put your header and data into a dataframe, and then use the .to_csv method on that dataframe. Csv can get tricky when you have strings that contain commas, etc...
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html
