I have 25 .csv files (each file is a scribe) all in same structure (X, Y and STATUE). I want to combine all of them into one large .txt file

Question

So I have tried this and got all the files (25 scribes files) combine into one. Each scribe contains 3330 ID number and there is an co ordinate X and Y to highlight the number of defects (STATUE) for each ID number. I want to know the total sum of STATUE for each ID number from all the files combined.

import os
import pandas as pd
from glob import glob

stock_files = sorted(glob('*AVI.als'))
dfList = []
stock_files


df = pd.concat((pd.read_csv(file).assign(filename = file) for file in stock_files), ignore_index = True)




X\tY\tSTATUS    filename
0   14\t1\t0    2008-09728-AVI.als
1   15\t1\t0    2008-09728-AVI.als
2   16\t1\t0    2008-09728-AVI.als
3   17\t1\t0    2008-09728-AVI.als
4   18\t1\t0    2008-09728-AVI.als
... ... ...
83245   30\t90\t0   2008-13754-AVI.als
83246   31\t90\t0   2008-13754-AVI.als
83247   32\t90\t0   2008-13754-AVI.als
83248   33\t90\t0   2008-13754-AVI.als
83249   34\t90\t0   2008-13754-AVI.als

for all CSV files combine into one.txt file, I should see the result like this below

X  Y STATUS
0   14 1 0
1   15 1 0  
2   16 1 0  
3   17 1 0
4   18 1 0
...
3330

Any help is much appreciated

Answer 1

I think you simply need to add the separator (sep=r"\t"):

df = pd.concat([pd.read_csv(file, sep=r"\t").assign(filename = file) for file in stock_files], ignore_index = True)

You can simply save to.txt like this:

df.to_csv("output.txt")

If you want the sum of STATUS for each ID (X) you can do this:

df.groupby(["X"])["STATUS"].sum()