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      <title>Webscraping IMDB  by Nur Davlatov</title>
      <link>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3</link>
      <description></description>
      <language>en-us</language>
      <pubDate>2021-08-05 18:37:42 UTC</pubDate>
      <lastBuildDate>2026-02-05 20:59:29 UTC</lastBuildDate>
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         <title>What is the goal of our project?</title>
         <author>ndavlatow</author>
         <link>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670293641</link>
         <description><![CDATA[<div>We want to create a project which can help us organize the data being displayed on the IMDB Top 1000 Movie website. Therefore, our goal is it to organize the different variables into different groups such as titles, ranking, turnover etc.&nbsp;</div>]]></description>
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         <pubDate>2021-08-05 18:48:45 UTC</pubDate>
         <guid>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670293641</guid>
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         <title>How did we do it? </title>
         <author>ndavlatow</author>
         <link>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670294125</link>
         <description><![CDATA[<div>We started creating a project in python. Then we first inspected the website. In our project, we then imported BeautifulSoup, Pandas, and Numpy. Then we used the URL from the IMDB website. We requested to get the URL to get access to the webpage and we used BeautifulSoup to get access of the content that we want to extract from the webpage. Afterwards we initiated the lists for the information we wanted to get from the IMDB website, that is, titles, years, time, IMDB ratings, metascores, votes, and the gross revenue. Then we looked for the class we needed.&nbsp;</div>]]></description>
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         <pubDate>2021-08-05 18:49:30 UTC</pubDate>
         <guid>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670294125</guid>
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         <title>How we proceeded</title>
         <author>ndavlatow</author>
         <link>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670294727</link>
         <description><![CDATA[<div>Then we initiated the loop to get all the date from each of the movies, and we then stored every div container in movie_div.<br><br>We then build our pandas dataframe.&nbsp;<br><br>After collecting the data we had to clean the data with pandas. After we only needed to export the data into a CSV file, and that’s it.&nbsp;</div>]]></description>
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         <pubDate>2021-08-05 18:50:24 UTC</pubDate>
         <guid>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670294727</guid>
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      <item>
         <title>The Result</title>
         <author>ndavlatow</author>
         <link>https://padlet.com/ndavlatow/q3c7tf36ffosb5j3/wish/1670294983</link>
         <description><![CDATA[<div>Now we can successfully see the different variables we were looking for in an ordered manner. This allows us to easily look for different variables in movies.</div>]]></description>
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         <pubDate>2021-08-05 18:50:46 UTC</pubDate>
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