将以逗号分隔的单词读入熊猫

Question

I have a file filled with words like so :

words.txt

"A", "B", "C", "D", "E",
"F", "G", "H", "I", "J",
"K", "L", "M", "N", "O"

How can I read this file using Pandas? My ultimate goal would be a series that contained (A, B, C, D, E. . .O)

read_csv seems geared towards a table.

I managed to accomplish this using

words = list(pd.read_csv('words.txt').columns)

But this is so ugly. I'm sure there's a better way.

Thank you!

Answer 1

This would be an answer

list = ["A", "B", "C", "D", "E","F", "G", "H", "I", "J","K", "L", "M", "N", "O"]

print(list)

Output:

['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O']

Answer 2

使用纯python，您可以执行以下操作来建立列表：

words = [word.strip() for line in open("words.txt") for word in line.split(",") if word]

Answer 3

You do not need pandas library for this alone, you can simply use the csv module for this. Example -

import csv
with open('<csvfile>','r') as f:
    reader = csv.reader(f,skipinitialspace=True)
    words = next(reader)

skipinitialspace is to skip the whitespace after the delimiter , which seems to be there in your csv.

---

Example/Demo -

My a.csv -

"A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O"

Code and result -

>>> import csv
>>> with open('a.csv','r') as f:
...     reader = csv.reader(f,skipinitialspace=True)
...     words = next(reader)
...
>>> words
['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O']