使用 python 将 Txt 转换为 Xlsx

Question

I'm very new to python. But I'm trying to build a code that will convert text files to xlsx. It has to be xlsx because there's too many entries for xls and I can't just convert it to csv because there's two fields that don't get read correctly if I do.

This is what I have and it works...eventually. It is extremely slow. I've tried looking up other codes online and I can't get any of them to work for me. Like I said, I'm very new to this. Any suggestions on how to speed this up?

import pandas as pd

nal = pd.read_csv('Path.TXT', delimiter= '\t') 
nal.columns = ['1','2','3',...]
nal.to_excel('path.xlsx', 'Sheet 1')

Edit: I have no idea how to attach the files I'm working with. They're tab delimited. Here's one file's set-up

   10001    2020    30380000001006000001.0  "CR 512    SEBASTIAN, FL 32958" 12/11/2014  FLEMING GRANT PLAT SHOWING THE S/D OF PBB 1-72 BEING MORE PART DESC AS FOLL ALL THAT PART FLEMING GRANT SEC 6 & 15 LYING S OF FELLSMERE WATER CONT ROL DISTRICT MAIN OUTFALL CANAL & LYINGS OF TWP LINE BETWEEN TWP 30S & TWP 31S (SAME BEING THE N BDRY OF IND 00  30  38          COMM    MULTI   0.00000 690102.10   69          1   1083.5100   3038000001  FLEMING GRANT                   120610509041        1   72          "FLEMING GRANT PLAT SHOWING THE S/D OF PBB 1-72 BEING MORE PART DESC AS FOLL ALL THAT PART FLEMING GRANT SEC 6 & 15 LYING S OF FELLSMERE WATER CONT ROL DISTRICT MAIN OUTFALL CANAL & LYINGS OF TWP LINE BETWEEN TWP 30S & TWP 31S (SAME BEING THE N BDRY OF INDIAN RIVER C OUNTY) AS PROJECTED ACROSS THE FLEMING GRANT: LESS & EXCEPTING THAT PART OF SAID FLEMING GRANT SEC 6 DESC AS FOLL: BEG AT INTERSECTION OF FLEMING GRANT LINE & SR/W OF 400 FT WIDE R/W OF FELLSMERE MAIN OUTFALL CANAL, RUN TH S 89 DEG 49 MIN 55 SEC E ALONG SAID S R/W FELLSMERE MAINCANAL, A DIST OF 829.06 FT TO A PT OF INTERSECTION WITH E LINE OF A 170 FT WIDE FP&L TRANSMISSION LINE EASEMENT; TH RUNS 18 DEG 46 MIN 02 SEC E ALONG E LINE OF SAID EASEMENT A DIST OF 1073.84 FT; TH RUN N 89 DEG 26 MIN 54 SEC W A DIST OF166.10 FT TO A PT ON FLEMING GRANT LINE; TH RUN N 44 DEG 44 MIN 30 SEC W ALONG SAID FLEMING GRANT LINE A DIST OF 1432.63FT TO POB. (PCL 2 IN OR BK 1304 PP 2778)"

10002   2020    30380000001006000002.0  "CR 512    SEBASTIAN, FL 32958" 11/07/2012  FLEMING GRANT PLAT SHOWING THE S/D OF PBB 1-72 BEING MORE PART DESC AS FOLL PART OF GRANT SEC 6 AS IN D BK10 PP 473 ST LUCIE CO RECORDS 00  30  38          COMM    MULTI   0.00000 710102.10   71          1   15.2200 3038000001  FLEMING GRANT                   120610509041        1   72          FLEMING GRANT PLAT SHOWING THE S/D OF PBB 1-72 BEING MORE PART DESC AS FOLL PART OF GRANT SEC 6 AS IN D BK10 PP 473 ST LUCIE CO RECORDS

Here's the other file's set-up:

41  30380000001006000001.0  R   2020    087         2762951         2762951 2762951 0   0   0   0   0   0   2762951 2762951 0   0   0   0   0   0   0   0   0   0   0   0   0   0               2762951 1   1083.51 47197696                    1214    0   0   0       ST JOHNS RIVER WATER MANAGEMEN  PO BOX 1429     PALATKA FL  32178   FL                              FLEMING GRANT PLAT SHOWING THE      XXXXXXXXX       XXXXXXXXX       69  690102.10   W   1   30  38  00  120610509041    CR 512      SEBASTIAN   32958   10001   

41  30380000001006000002.0  R   2020    094         0           0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0               0   6       662983                  1112    0   0   0       FELLSMERE DR DIST   CR 512      SEBASTIAN   FL  32958   FL                              FLEMING GRANT PLAT SHOWING THE      XXXXXXXXX       XXXXXXXXX       71  710102.10       1   30  38  00  120610509041    CR 512      SEBASTIAN   32958   10002                               10002   2

Answer 1

Try this

mypath = "C:/Users/Test/Downloads/Data/" #path where you saved the text files

files = [join(mypath, f) for f in listdir(mypath) if isfile(join(mypath, f))]
for txt in files:
    with open(txt) as fp:
        lst = [row.split("\t") for row in fp.read().split("\n")]
        col = list(range(1, len(lst[0])+1))
        df = pd.DataFrame(lst, columns=col)
        df.to_excel(ntpath.basename(txt)[:-4] + ".xlsx")