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Houses_in_Nigeria.Rmd

Houses_in_Nigeria.html

Nigeria_Agric_Export_Analysis.Rmd

Nigeria_Agric_Export_Analysis.html

Nigeria_Agric_Export_Analysis.pbix

Order and Sales Analysis.pbix

README.md

Retail Strategy Analytics 1.Rmd

Sales_Intro.Rmd

Sales_Intro.html

Scraping_a_Table.py

hospital_patients_analysis.sql

nigeria_houses.sql

/

30 lines (22 loc) · 814 Bytes

from bs4 import BeautifulSoup import pandas as pd import requests url = "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue" page = requests.get(url) soup = BeautifulSoup(page.text, "html.parser") table = soup.find_all("table")[0] rows = table.find_all("tr") table_header = table.find_all("th")[0:7] clean_table_header = [header.text.strip() for header in table_header] df = pd.DataFrame(columns= clean_table_header) for row in rows[1:]: columns = row.find_all("td") if len(columns)>= 7: row_data = [data.text.strip() for data in columns[:7]] length = len(df) df.loc[length] = row_data df.to_csv("Top_companies.csv", index=False, encoding= 'utf-8') df.info() print(clean_table_header) table_header clean_table_header

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