Answered: 2. Using this website:…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

https://en.wikipedia.org/wiki/Greenhouse_gas

Webscraping class:

class WebScraping:
def __init__(self,url):
self.url = url
self.response = requests.get(self.url)
self.soup = BeautifulSoup(self.response.text, 'html.parser')

def extract_data(self):
data = defaultdict(list)
table = self.soup.find('table', {'class': 'wikitable sortable'})
rows = table.find_all('tr')[1:]
for row in rows:
cols = row.find_all('td')
data['Country Name'].append(cols[0].text.strip())
data['1980'].append(cols[1].text.strip())
data['2018'].append(cols[2].text.strip())
return data

question #1

class GreenhouseGasData(NamedTuple):

Gas: str

Pre_1750: float

Recent: float

Absolute_increase_since_1750: float

Percentage_increase_since_1750: float

class GreenhouseGasCollection:

def __init__(self, data):

self.data = data

def __repr__(self):

return str(self.data)

def sort_by(self, column):

if column not in GreenhouseGasData._fields:

raise ValueError(f"{column} not found in {GreenhouseGasData._fields}")

# self.data = sorted(self.data, key=lambda x: x[column])

self.data = sorted(self.data, key=lambda x: getattr(x, column))

def search(self, gas):

for gas_data in self.data:

if gas_data.Gas == gas:

return gas_data

return None

def main():

data = [

GreenhouseGasData("Carbon dioxide", 280, 414.8, 134.8, 48.0),

GreenhouseGasData("Methane", 722, 1874.0, 1152.0, 159.0),

GreenhouseGasData("Nitrous oxide", 270, 329.0, 59.0, 21.9),

GreenhouseGasData("Fluorinated gases", 0.5, 13.0, 12.5, 2500.0),

]

collection = GreenhouseGasCollection(data)

print("Data:", collection)

collection.sort_by("Recent")

print("Data sorted by Recent:", collection)

result = collection.search("Carbon dioxide")

if result:

print("Data for Carbon dioxide:", result)

else:

print("Data for Carbon dioxide not found")

if __name__ == "__main__":

main()

2. Using this website:
https://en.wikipedia.org/wiki/Greenhouse_gas
and using your Webscraping
class from labo, scrape the Concentrations Table and store the data in your named tuple class
defined in question #1. Store each tuple class object in a cumulative dataframe.

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