Scrapy - how to index and extract from html tables - html

Question

This is the webpage I am scraping: http://laxreports.sportlogiq.com/nll/GS2200.html
Below is the code for the spider I created:
import scrapy
class MatchesSpider(scrapy.Spider):
name = 'matches'
allowed_domains = ['laxreports.sportlogiq.com']
start_urls = ['http://laxreports.sportlogiq.com/nll/GS2200.html']
def parse(self, response):
tables = response.xpath('//table')
print(tables)
table = tables[0].xpath('//tbody')
I see 22 tables that have been selected for this XPath expression but my problem is that I don't fully understand how to select each individual table and extract its contents.
I am a beginner in scrapy and after searching online for a solution all I see is how to select the tables using the class or ID which in this case is not an option.

Answer 1

You can do that using only pandas
Code:
import pandas as pd
dfs = pd.read_html('https://laxreports.sportlogiq.com/nll/GS2200.html')
df = dfs[10]#.to_csv('d.csv', index = False)
print(df)
Output:
0 1 2 3 4 5 6 7 8 9 10 11 12
0 # Name G A +/- PIM S SOFF LB T CT FO TOF
1 2 W.Malcom 0 0 0 0 1 1 1 4 0 - 11:28
2 3 T.Edwards 0 0 -2 2 0 0 8 1 2 7-18 20:28
3 4 J.Sullivan 0 0 -3 2 0 0 3 0 0 - 15:29
4 11 T.Stuart 0 0 -3 0 0 0 4 1 1 - 21:09
5 14 W.Jeffrey 0 1 -1 0 0 0 9 2 1 - 19:17
6 16 R.Lee 2 1 2 0 9 4 6 6 1 - 23:13
7 17 C.Wardle 2 0 1 2 5 3 4 2 2 - 20:55
8 18 R.Hope (A) 0 0 -2 2 0 0 11 0 0 - 22:02
9 20 J.Ruest 3 2 3 0 8 1 3 2 0 - 24:16
10 23 J.Gilles 0 0 -1 0 0 0 4 0 3 - 14:44
11 27 S.Carnegie 0 0 -1 0 0 0 3 0 0 - 12:19
12 37 D.Coates (C) 0 0 0 0 1 0 1 0 0 1-1 2:31
13 51 E.McLaughlin 0 5 2 0 7 3 5 7 0 - 21:41
14 55 D.Kinnear 0 1 2 0 2 0 2 1 0 0-2 10:14
15 67 K.Killen 1 1 0 0 6 1 4 2 0 - 16:42
16 82 J.Cupido (A) 0 1 -1 0 3 0 4 1 0 - 20:52
17 86 J.Lintz 0 1 -1 0 0 0 4 0 1 - 19:26
18 30 T.Carlson 0 0 NaN 0 0 0 0 0 0 - NaN
19 45 D.Ward 0 0 NaN 0 0 0 0 1 0 - NaN
20 NaN Totals: 8 13 NaN 8 42 13 76 30 11 8-21 NaN