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Updated 3 months ago

<@334536717648265216> trying to do webscraping for https://en.wikipedia.org/wiki/2020%E2%

trying to do webscraping for https://en.wikipedia.org/wiki/2020%E2%80%9321_Premier_League to extract the table data, love to see what sources are available?
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3 comments
Please stand by @andysingal as I search the knowledge base. I normally take about 20 seconds or so. :wave:
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I'm sorry, but the information extracts provided do not contain specific details on how to perform web scraping for the Premier League data from Wikipedia using LlamaIndex. However, LlamaIndex does provide a way to load data from Wikipedia pages as shown in the extracts. Here's an example of how you can load data from a Wikipedia page:

Plain Text
from llama_index import download_loader

WikipediaReader = download_loader("WikipediaReader")

loader = WikipediaReader()

documents = loader.load_data(pages=["2023 in science"], auto_suggest=False)

In this example, the page "2023 in science" is loaded. You can replace this with your desired Wikipedia page. Please note that this might not directly extract table data, but it will load the content of the page.

For more specific instructions on how to use LlamaIndex for your use case, I would recommend referring to the LlamaIndex documentation () or the LlamaIndex GitHub repository () for more examples and details.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@Logan M the information shared does not assist to extract:
Plain Text
 [{'name': 'Manchester City (C)', 'scored': 83},
 {'name': 'Manchester United', 'scored': 73},
 {'name': 'Liverpool', 'scored': 68},
 {'name': 'Chelsea', 'scored': 58},
 {'name': 'Leicester City', 'scored': 68},
 {'name': 'West Ham United', 'scored': 62},
 {'name': 'Tottenham Hotspur', 'scored': 68},
 {'name': 'Arsenal', 'scored': 55},
 {'name': 'Leeds United', 'scored': 62},
 {'name': 'Everton', 'scored': 47},
 {'name': 'Aston Villa', 'scored': 55},
 {'name': 'Newcastle United', 'scored': 46},
 {'name': 'Wolverhampton Wanderers', 'scored': 36},
 {'name': 'Crystal Palace', 'scored': 41},
 {'name': 'Southampton', 'scored': 47},
 {'name': 'Brighton & Hove Albion', 'scored': 40},
 {'name': 'Burnley', 'scored': 33},
 {'name': 'Fulham (R)', 'scored': 27},
 {'name': 'West Bromwich Albion (R)', 'scored': 35},
 {'name': 'Sheffield United (R)', 'scored': 20}]
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