IMDB movies Year wise Rating Comparison (Data Analysis) Python

Code:

import requests

import bs4

from matplotlib import pyplot as plt

yearDict={}

def fetch(year,counting=100):

res=requests.get("https://www.imdb.com/search/title?count="+str(counting)+"&genres=action&release_date="+str(year)+","+str(year)+"&title_type=feature");

soup=bs4.BeautifulSoup(res.text,'lxml')

moviesList=soup.findAll("div",{"class":"lister-item mode-advanced"})

count=0

sum=0

for i in moviesList:

value=i.find("div",{"class":"inline-block ratings-imdb-rating"})

# year=i.find("span",{"class":"lister-item-year text-muted unbold"}).text

if value is not None:

count=count+1

sum=sum+float(value['data-value'])

# print(i.find("h3",{"class":"lister-item-header"}).text)

# print(i.find("div",{"class":"inline-block ratings-imdb-rating"})['data-value'])

print(year,{"sum":sum,"count":count,"total":len(moviesList)})

return {"sum":sum,"count":count,"total":len(moviesList)}

# print("Total is ",sum)

# print("Average is ",sum/count)

years=[2015,2016,2017,2018]

for i in years:

yearDict[i] = fetch(i)

print(yearDict)

averages=[]

for i in years:

averages.append(yearDict[i]['sum']/yearDict[i]['count'])

# plt.scatter(years, averages, label="Movies", color='r')

# plt.bar(years,averages)

# cols = ['r', 'g', 'b','y']

# explode = (0.1, 0, 0,0.1)

# plt.pie(averages,

# labels=years,

# colors=cols,

# startangle=180,

# shadow=True,

# explode=explode

# )

plt.plot(years,averages,'c', label="Movies", linewidth=2)

plt.legend()

plt.title("Movies")

plt.xlabel("Years")

plt.ylabel("Averages")

plt.grid(True,color='g')

plt.show()

NOTE: You can pass count to the fetch function to get analysis to that much movies

 

Screenshots: