如何在 Python 中将多个 .txt 文件转换为 .csv 文件

Question

我正在尝试使用 Python 将多个文本文件转换为单个 .csv 文件。我目前的代码是这样的：

import pandas
import glob

#Collects the files names of all .txt files in a given directory.
file_names = glob.glob("./*.txt")

#[Middle Step] Merges the text files into a single file titled 'output_file'.
with open('output_file.txt', 'w') as out_file:
    for i in file_names:
        with open(i) as in_file:
            for j in in_file:
                out_file.write(j)

#Reading the merged file and creating dataframe.
data = pandas.read_csv("output_file.txt", delimiter = '/')
  
#Store dataframe into csv file.
data.to_csv("convert_sample.csv", index = None)

如您所见，我正在读取所有文件并将它们合并到一个 .txt 文件中。然后我将其转换为单个 .csv 文件。有没有办法在没有中间步骤的情况下做到这一点？是否有必要将我所有的 .txt 文件连接成一个 .txt 以将其转换为 .csv，或者有没有办法将多个 .txt 文件直接转换为一个 .csv？

非常感谢。

Answer 1

当然可以。而且你真的不需要在这里涉及pandas，只需使用标准库csv 模块即可。如果你提前知道列名，最轻松的方法是使用csv.DictWriter和csv.DictReader对象：

import csv
import glob

column_names = ['a','b','c'] # or whatever


with open("convert_sample.csv", 'w', newline='') as target:
    writer = csv.DictWriter(target, fieldnames=column_names)
    writer.writeheader() # if you want a header
    for path in glob.glob("./*.txt"):
        with open(path, newline='') as source:
            reader = csv.DictReader(source, delimiter='/', fieldnames=column_names)
            writer.writerows(reader)