35 lines
1 KiB
Python
35 lines
1 KiB
Python
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import requests
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import pandas as pd
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from bs4 import BeautifulSoup
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import pycountry
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import json
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import os
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# Fetch and parse the website
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response = requests.get('https://www.statista.com/statistics/268136/top-15-countries-based-on-number-of-facebook-users/')
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content = response.content
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soup = BeautifulSoup(content, 'html.parser')
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# Find all of the data points
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tds = soup.select('#statTableHTML td')
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# Frame the data
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data = []
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def population(country):
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countryCode = pycountry.countries.search_fuzzy(country)[0].alpha_3
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res = requests.get('https://restcountries.eu/rest/v2/alpha/' + countryCode)
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return json.loads(res.content)['population']
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for td1, td2 in zip(tds[::2], tds[1::2]):
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frame = {}
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frame['country'] = td1.text.strip()
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frame['active'] = td2.text.strip()
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frame['population'] = population(frame['country'])
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frame['percentActive'] = (int(frame['active']) * 1000000 / int(frame['population'])) * 100
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data.append(frame)
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# Save the data
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df = pd.DataFrame(data)
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df.to_csv(os.path.dirname(os.path.realpath(__file__)) + '/fbPercentActive_res.csv')
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