Kursinhalt
Web Scraping with Python
Web Scraping with Python
Simple Solution for Scraping
The library pandas provide a quick and convenient solution for converting HTML tables to the DataFrame. The function read_html() can be useful for scraping tables from various websites without figuring out how to get the website’s HTML. You can use read_html() to work with tables whose structure is not complicated, for example, tables on Wikipedia pages.
import pandas as pd tables = pd.read_html('https://en.wikipedia.org/wiki/Florida')
In the code above, the function read_html() got all tables from Wiki about Florida. table is a list of all the tables on the page already converted to DataFrames.
With a large number of tables on the page, it can be challenging to find the one you need. To make the table selection easier, use the match parameter to select the table you want. For example:
import pandas as pd tables = pd.read_html('https://en.wikipedia.org/wiki/Florida', match='State University System of Florida')
Swipe to start coding
Get the table from the Wikipedia page about Florida and convert it to the DataFrame.
- Import
pandaslibrary with thepdalias. - Get the table 'Largest cities or towns in Florida' from the page.
- Print the DataFrame df.
Lösung
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwendenDanke für Ihr Feedback!
Simple Solution for Scraping
The library pandas provide a quick and convenient solution for converting HTML tables to the DataFrame. The function read_html() can be useful for scraping tables from various websites without figuring out how to get the website’s HTML. You can use read_html() to work with tables whose structure is not complicated, for example, tables on Wikipedia pages.
import pandas as pd tables = pd.read_html('https://en.wikipedia.org/wiki/Florida')
In the code above, the function read_html() got all tables from Wiki about Florida. table is a list of all the tables on the page already converted to DataFrames.
With a large number of tables on the page, it can be challenging to find the one you need. To make the table selection easier, use the match parameter to select the table you want. For example:
import pandas as pd tables = pd.read_html('https://en.wikipedia.org/wiki/Florida', match='State University System of Florida')
Swipe to start coding
Get the table from the Wikipedia page about Florida and convert it to the DataFrame.
- Import
pandaslibrary with thepdalias. - Get the table 'Largest cities or towns in Florida' from the page.
- Print the DataFrame df.
Lösung
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwendenDanke für Ihr Feedback!
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwenden