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How to Scrape Data Off Wikipedia: Three Ways (No Code and Code)

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Manage episode 431877236 series 3474159
Kandungan disediakan oleh HackerNoon. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh HackerNoon atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-scrape-data-off-wikipedia-three-ways-no-code-and-code.
Get your hands on excellent manually annotated datasets with Google Sheets or Python
Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #python, #google-sheets, #data-analysis, #pandas, #data-scraping, #web-scraping, #wikipedia-data, #scraping-wikipedia-data, and more.
This story was written by: @horosin. Learn more about this writer by checking @horosin's about page, and for more stories, please visit hackernoon.com.
For a side project, I turned to Wikipedia tables as a data source. Despite their inconsistencies, they proved quite useful. I explored three methods for extracting this data: - Google Sheets: Easily scrape tables using the =importHTML function. - Pandas and Python: Use pd.read_html to load tables into dataframes. - Beautiful Soup and Python: Handle more complex scraping, such as extracting data from both tables and their preceding headings. These methods simplify data extraction, though some cleanup is needed due to inconsistencies in the tables. Overall, leveraging Wikipedia as a free and accessible resource made data collection surprisingly easy. With a little effort to clean and organize the data, it's possible to gain valuable insights for any project.

  continue reading

346 episod

Artwork
iconKongsi
 
Manage episode 431877236 series 3474159
Kandungan disediakan oleh HackerNoon. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh HackerNoon atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-scrape-data-off-wikipedia-three-ways-no-code-and-code.
Get your hands on excellent manually annotated datasets with Google Sheets or Python
Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #python, #google-sheets, #data-analysis, #pandas, #data-scraping, #web-scraping, #wikipedia-data, #scraping-wikipedia-data, and more.
This story was written by: @horosin. Learn more about this writer by checking @horosin's about page, and for more stories, please visit hackernoon.com.
For a side project, I turned to Wikipedia tables as a data source. Despite their inconsistencies, they proved quite useful. I explored three methods for extracting this data: - Google Sheets: Easily scrape tables using the =importHTML function. - Pandas and Python: Use pd.read_html to load tables into dataframes. - Beautiful Soup and Python: Handle more complex scraping, such as extracting data from both tables and their preceding headings. These methods simplify data extraction, though some cleanup is needed due to inconsistencies in the tables. Overall, leveraging Wikipedia as a free and accessible resource made data collection surprisingly easy. With a little effort to clean and organize the data, it's possible to gain valuable insights for any project.

  continue reading

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