示例数据集:
120GB Hard Disk Drive with 3 Years Warranty for Lenovo Essential B570 Laptop Notebook HDD Computer - Certified 3 Years Warranty from Seifelden 3950 8
"TOSHIBA SATELLITE L305-S5919 LAPTOP LCD SCREEN 15.4"" WXGA CCFL SINGLE SUBSTITUTE REPLACEMENT LCD SCREEN ONLY. NOT A LAPTOP" 35099 324
Hobby-Ace Pixhawk PX4 RGB External LED Indicator USB Module for Pixhawk Flight Controller 21822 510
Pelicans mousepad 44629 260
P4648-60029 Hewlett-Packard Tc2100 System Board 42835 68
Ectaco EI900 SD Card English - Italian 249 6
Zippered Pocket Black School Laptop Tablet Dual Straps Deluxe Backpack 4342 172
这里我想分成三列
第1列为Product_id - 联想Essential B570笔记本电脑硬盘电脑提供3年保修120GB硬盘 - Seifelden认证3年保修
第2列为order_id 3950
第3列为item_id 8
同样我需要我的所有数据集
答案 0 :(得分:1)
如果您不介意使用库,pandas可以读取csvs和tsvs。你想要
import pandas
df = pandas.read_csv('<your file>', sep='\t', names=['Product_id', 'order_id', 'item_id'])
如果你想使用vanilla python,它有点复杂,但this stackoverflow question有可能有用的代码片段。
答案 1 :(得分:1)
您可以使用csv
模块来读取文件:
import csv
from pprint import pprint
columns = 'Product_id order_id item_8'.split()
with open('data.tsv', 'rb') as tsv_file:
for row in csv.DictReader(tsv_file, fieldnames=columns, delimiter='\t'):
pprint(row)
输出:
{'Product_id': '120GB Hard Disk Drive with 3 Years Warranty for Lenovo Essential B570 Laptop Notebook HDD Computer - Certified 3 Years Warranty from Seifelden',
'item_8': '8',
'order_id': '3950'}
{'Product_id': 'TOSHIBA SATELLITE L305-S5919 LAPTOP LCD SCREEN 15.4" WXGA CCFL SINGLE SUBSTITUTE REPLACEMENT LCD SCREEN ONLY. NOT A LAPTOP',
'item_8': '324',
'order_id': '35099'}
{'Product_id': 'Hobby-Ace Pixhawk PX4 RGB External LED Indicator USB Module for Pixhawk Flight Controller',
'item_8': '510',
'order_id': '21822'}
{'Product_id': 'Pelicans mousepad', 'item_8': '260', 'order_id': '44629'}
{'Product_id': 'P4648-60029 Hewlett-Packard Tc2100 System Board',
'item_8': '68',
'order_id': '42835'}
{'Product_id': 'Ectaco EI900 SD Card English - Italian',
'item_8': '6',
'order_id': '249'}
{'Product_id': 'Zippered Pocket Black School Laptop Tablet Dual Straps Deluxe Backpack',
'item_8': '172',
'order_id': '4342'}