使用 pandas 将文本文件列转换为 csv 文件单行？

Question

I have text file which look like this: txt file

Now I want to convert that text file in csv file single row

The outcome would look like: output

This is my code:

with open("file.txt", "r") as fin,\
     open("file.csv", "w") as fout:
    col1, col2,col3,col4 = zip(*(line.rstrip().split() for line in fin))
    fout.write(",".join(col1 + col2 +col4 +col5))

textfile:

 data1 data5 data9 data13 data2 data10 data14 data data7 data11 data15 data4 data12 data16 1 5 9 13 2 10 14 3 7 11 15 4 12 16 output: data1 data2 data3 data4 data5 data7 data10 data11.... data16 1 2 3 4 5 7 10 11.... 16

Answer 1

Try the following approach:

1. Use a regular expression to pick out all the entries.
2. Split the list in two and sort the pairs based on the numeric value found in each 'header' value. Conversion to integer is needed to avoid data10 being sorted before data1 .
3. Build a list of the sorted key value pairs.
4. Use a csv.writer() to create the CSV file by transposing the entries into two rows.

For example:

import re
import csv

with open('file.txt') as f_input:
    data = re.findall('\w+', f_input.read())
    items = len(data) // 2

with open('file.csv', 'w', newline='') as f_output:    
    kv = [(k, v) for k, v in sorted(zip(data[:items], data[items:]), key=lambda x: int(re.search('\d+', x[0]).group(0)))]
    csv.writer(f_output).writerows(zip(*kv))

Giving you file.csv containing:

data1,data2,data3,data4,data5,data7,data9,data10,data11,data12,data13,data14,data15,data16
1,2,3,4,5,7,9,10,11,12,13,14,15,16