使用Python Loop从Excel文件创建多个.txt文件

Question

My work is in the process of switching from SAS to Python and I'm trying to get a head start on it. I'm trying to write separate .txt files, each one representing all of the values of an Excel file column.

I've been able to upload my Excel sheet and create a .txt file fine, but for practical uses, I need to find a way to create a loop that will go through and make each column into it's own .txt file, and name the file "ColumnName.txt".

Uploading Excel Sheet:

import pandas as pd

wb = pd.read_excel('placements.xls')

Creating single .txt file: (Named each column AZ for easy reference)

with open("A.txt", "w") as f:

for item in wb['A']:
    f.write("%s\n" % item)

Trying my hand at a for loop (to no avail):

import glob

for file in glob.glob("*.txt"):

    f = open(( file.rsplit( ".", 1 )[ 0 ] ) + ".txt", "w") 
    f.write("%s\n" % item)
    f.close()

The first portion worked like a charm and gave me a .txt file with all of the relevant data.

When I used the glob command to attempt making some iterations, it doesn't error out, but only gives me one output file (A.txt) and the only data point in A.txt is the letter A. I'm sure my inputs are way off... after scrounging around forever it's what I found that made sense and ran, but I don't think I'm understanding the inputs going in to the command, or if what I'm running is just totally inaccurate.

Any help anyone would give would be much appreciated! I'm sure it's a simple loop, just hard to wrap your head around when you're so new to python programming.

Thanks again!

Answer 1

I suggest use pandas for write files by to_csv , only change extension to .txt :

# Uploading Excel Sheet:
import pandas as pd

df = pd.read_excel('placements.xls')

# Creating single .txt file: (Named each column A-Z for easy reference)

for col in df.columns:
    print (col)
    #python 3.6+ 
    df[col].to_csv(f"{col}.txt", index=False, header=None)
    #python bellow
    #df[col].to_csv("{}.txt".format(col), index=False, header=None)