netflix shows dataset

Data Cleaning means the process of identifying incorrect, incomplete, inaccurate, irrelevant, or missing pieces of data and then modifying, replacing, or deleting them as needed. International Movies is a genre that is mostly in Netflix. Since “director,” “cast,” and “country” contain the majority of null values, we chose to treat each missing value is unavailable. The charts are grouped in components and can be displayed locally or from the WebPortal. Netflix is a streaming service that offers a wide variety of award-winning TV shows, movies, anime, documentaries, and more on thousands of internet-connected devices. Next, we will explore the amount of content Netflix has added throughout the previous years. My own viewing activity data, for example, was over 27,000 rows long. The other two label “date_added” and “rating” contain an insignificant portion of the data, so it drops from the dataset. Additional Project Details Intended Audience Science/Research, Developers Programming Language Python, Perl, C++, C Registered 2008-11-04 Similar Business Software. The dataset you'll get from Netflix includes every time a video of any length played — that includes those trailers that auto-play as you're browsing your list. How many electric vehicles can our current supply of lithium power? even on https://web.archive.org/web/20090926031123/http://archive.ics.uci.edu/ml/machine-learning-databases/netflix. Open Data Stack Exchange is a question and answer site for developers and researchers interested in open data. Making statements based on opinion; back them up with references or personal experience. Fact checked. The top actor on Netflix Movies, based on the number of titles, is Anupam Kher. Netflix is a popular entertainment service used by people around the world. Command parameters & arguments - Correct way of typing? When trying to fry onions, the edges burn instead of the onions frying up. MovieID1: CustomerID11,Date11 CustomerID12,Date12 … MovieID2: CustomerID21,Date21 CustomerID22,Date22 For the Netflix Prize, your program must predic… site design / logo © 2020 Stack Exchange Inc; user contributions licensed under cc by-sa. There are a few columns that contain null values, “director,” “cast,” “country,” “date_added,” “rating.”. Finally, we can see that there are no more missing values in the data frame. Data Cleansing is considered as the basic element of Data Science. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. Is it true that an estimator will always asymptotically be consistent if it is biased in finite samples? Latest news from Analytics Vidhya on our Hackathons and some of our best articles! Disney+; Amazon Prime; Blinkbox ; CinemaNow; Google Play; hayu; iTunes; MUBI; NOW TV; … “TV-MA” is a rating assigned by the TV Parental Guidelines to a television program designed for mature audiences only. An example of one of the trailers Netflix used. The features I added to my dataset include genres, tags, and season number as categorical variables, and episode length as a numeric variable. I did not go into the dataset to check its validity but assuming it to be valid I chose too deep dive into it and see what intersting information and insights could be drawn out from the data. → 2. How to remove the core embed blocks in WordPress 5.6? I'd like to compare Netflix's series and movie offering (monthly or yearly) to see, over time, how their offering has diversified and changed, based on several metrics such as average show rating. I recently came across a dataset that had the viewers ratings of Netflix shows released by year. The most content type on Netflix is movies. 68% (4265) of which are movies and the rest of 1969 titles are classified as TV shows Lets’s take a quick look of the split of titles added every quarter from 2016Q1 to 2020Q1* (till Jan 18, 2020). Can use the dropna function from Pandas. Does a rotating rod have both translational and rotational kinetic energy? I'm not seeing the qualifying/test data anywhere, maybe Netflix never released that? Photograph: James Minchin/Netflix. TV Shows. Netflix and third parties use cookies and similar technologies on this website to collect information about your browsing activities which we use to analyse your use of the website, to personalise our services and to customise our online advertisements. It seems to have disappeared from the Internet. Netflix has to give recommendations for you from the 6000 movies that it's currently showing[1]. Learn more This workflow creates an interactive visualization dashboard of the "Netflix Movies and TV Shows" dataset. Learn more about our use of cookies and information. Is there any role today that would justify building a large single dish radio telescope to replace Arecibo? It appears that the Netflix data set is no longer available. rev 2020.12.10.38156, The best answers are voted up and rise to the top, Open Data Stack Exchange works best with JavaScript enabled, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site, Learn more about Stack Overflow the company, Learn more about hiring developers or posting ads with us. Is there an anomaly during SN8's ascent which later leads to the crash? The dataset consists of TV Shows and Movies available on Netflix as of 2019. In the following analysis, I used a dataset of 5000 recent reviews from the Netflix mobile app on Google Play. Netflix was founded in 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California. Is that the case, or is it still accessible somewhere? First let us take some time to go through the clustering algorithms. Netflix claims The Witcher is one of its most-watched shows, but the way Netflix now tracks views is much different than the way it used to. Data set having menu items (food) and corresponding image? Looking for a data-set of server performance data. Posted by. Next is exploring the countries by the amount of the produces content of Netflix. However, this wouldn’t be beneficial to our EDA since it is a loss of information. TV streaming; Sports streaming; Services. u/CarpeSeligit. The purpose of this dataset is to understand the rating distributions of Netflix shows. One of the canonical examples of a big data competition was the Netflix prize data set. Thanks for contributing an answer to Open Data Stack Exchange! Was Stan Lee in the second diner scene in the movie Superman 2? Netflix, Inc. is an American technology and media services provider and production company headquartered in Los Gatos, California. Top Actor on Netflix based on the number of titles. “TV-14” contains material that parents or adult guardians may find unsuitable for children under the age of 14. filtered_countries = netflix_df.set_index(‘title’).country.str.split(‘, ‘, expand=True).stack().reset_index(level=1, drop=True); filtered_countries = filtered_countries[filtered_countries != ‘Country Unavailable’], g = sns.countplot(y = filtered_countries, order=filtered_countries.value_counts().index[:15]), plt.title(‘Top 15 Countries Contributor on Netflix’), filtered_directors = netflix_df[netflix_df.director != 'No Director'].set_index('title').director.str.split(', ', expand=True).stack().reset_index(level=1, drop=True), plt.title('Top 10 Director Based on The Number of Titles'), sns.countplot(y = filtered_directors, order=filtered_directors.value_counts().index[:10], palette='Blues'). The dataset is collected from Flixable, which third-party Netflix search engine. http://archive.ics.uci.edu/ml/noteNetflix.txt, https://archive.org/details/nf_prize_dataset.tar, https://web.archive.org/web/20090925184737/http://archive.ics.uci.edu/ml/datasets/Netflix+Prize, https://web.archive.org/web/20090926031123/http://archive.ics.uci.edu/ml/machine-learning-databases/netflix, Podcast 293: Connecting apps, data, and the cloud with Apollo GraphQL CEO…. The popular streaming platform started gaining traction after 2014. The movie and customer ids are contained in the training set. From the info, we know that there are 6,234 entries and 12 columns to work with for this EDA. Do some exploratory data analysis on this dataset for practice. 1. We have drawn many interesting inferences from the dataset Netflix titles; here’s a summary of the few of them: You can download the data and python code document via my GitHub: https://github.com/dwiknrd/medium-code/tree/master/netflix-eda. From the README : The movie rating files contain over 100 million ratings from 480 thousand randomly-chosen, anonymous Netflix customers over 17 thousand movie titles. One of the canonical examples of a big data competition was the Netflix prize data set. In 2018, they released an interesting report which shows that the number of TV shows on Netflix has nearly tripled since 2010. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The country by the amount of the produces content is the United States. The training data is also now hosted on Kaggle. UNLIMITED TV SHOWS & MOVIES. Besides, we can know that Netflix has increasingly focused on movies rather than TV shows in recent years, → 3. As of Jan’2020, the dataset shows that Netflix has about a total of 6234 titles. This workflow creates a visualization dashboard of the "Netflix Movies and TV Shows" dataset. Of course the ratings are withheld. We need to separate all countries within a film before analyzing it, then removing titles with no countries available. Countries by the Amount of the Produces Content. The ratings include: G, PG, TV-14, TV-MA. You can watch as much as you want, whenever you want without a single commercial – all for one low monthly price. In this module, we will discuss the use of the fillna function from Pandas for this imputation. JOIN NOW SIGN IN. yeah, training data (nf_prize_dataset.tar.gz) is available, but testing data - no (grand_prize.tar.gz). Looking for Dataset of Netflix shows at certain points in time. Netflix supports the Digital Advertising Alliance Principles. The ratings are on a scale from 1 to 5 (integral) stars. Asking for help, clarification, or responding to other answers. Therefore, Netflix uses the only 2 or 3 shows you have watched to reward/ display/ recommend new shows to you. The most popular director on Netflix, with the most titles, is mainly international. show_id 6234 type 2 title 6172 director 3301 cast 5469 country 554 date_added 1524 release_year 72 rating 14 duration 201 listed_in 461 description 6226 dtype: int64 Check for Duplicate values ¶ In [8]: The company’s primary business is its subscription-based streaming service, which offers online streaming of a library of films and television series, including those produced in-house. Since then, the amount of content added has been increasing significantly. Take a look, netflix_df = pd.read_csv("netflix_titles.csv"), netflix_df.director.fillna("No Director", inplace=True), netflix_df.cast.fillna("No Cast", inplace=True), netflix_df.country.fillna("Country Unavailable", inplace=True), netflix_df.dropna(subset=["date_added", "rating"], inplace=True), plt.title(“Percentation of Netflix Titles that are either Movies or TV Shows”), g = plt.pie(netflix_df.type.value_counts(),explode=(0.025,0.025), labels=netflix_df.type.value_counts().index, colors=[‘red’,’black’],autopct=’%1.1f%%’, startangle=180), sns.lineplot(data=netflix_year_df, x=’year’, y=’date_added’), sns.lineplot(data=movies_year_df, x=’year’, y=’date_added’), sns.lineplot(data=shows_year_df, x=’year’, y=’date_added’), plt.title(“Total content added across all years (up to 2019)”). Named it with netflix_df for the dataset. Close. This dataset consists of tv shows and movies available on Netflix as of 2019. The country by the amount of the produces content is the United States. After a quick view of the data frames, it looks like a typical movie/TVshows data frame without ratings. From the images above, we can see the top 15 countries contributor to Netflix. Dataset from Netflix's competition to improve their reccommendation algorithm There are far more movie titles (68,5%) that TV shows titles (31,5%) in terms of title. Thanks! Looking for Dataset of Netflix shows at certain points in time. The following figure shows the daily number of reviews with a score of 1, it gives us an idea about the amount of data we are dealing with. Any idea if the qualifying ratings are available anywhere? Ever wondered why Netflix shows multiple artworks for a single TV show or movie? For a recommender system, is there a real data matrix that is about 500 by 500 that is complete and has no missing entries? As part of this data set, I took 4 videos from 4 ratings (totaling 16 unique shows), then pulled 53 suggested shows per video. csv files) from S3 to SQL Server and Amazon Redshift. Since Reinforcement learning happens in the absence of training dataset, its bound to learn from its own experience. So once Netflix suggests for you a movie and you watch it, it will again recommend you similar shows but if you don’t then it will change course. Do I need my own attorney during mortgage refinancing? - http://archive.ics.uci.edu/ml/noteNetflix.txt, BUT WAIT, there's more... perhaps it is available as an archive - https://archive.org/details/nf_prize_dataset.tar, BUT WAIT, EVEN MORE, it is also up on the archive in its true form: The growth in the number of movies on Netflix is much higher than that on TV shows. The largest count of Netflix content is made with a “TV-14” rating. User Based Movie Recommendation System based on Collaborative Filtering Using Netflix Movie Dataset. Imputation is a treatment method for missing value by filling it in using certain techniques. It consists of lines indicating a movie id, followed by a colon, and then customer ids and rating dates, one per line for that movie id. Netflix created 10 different advertisements to feature on the site. The data were collected between October, 1998 and December, 2005 and reflect the distribution of all ratings received during this period. The easiest way to get rid of them would be to delete the rows with the missing data for missing values. There are no empty lines in the file. The largest count of Netflix content is made with a “TV-14” rating. Netflix is a popular entertainment service used by people around the world. The dataset contains over 6234 titles, 12 descriptions. → 7. https://web.archive.org/web/20090925184737/http://archive.ics.uci.edu/ml/datasets/Netflix+Prize, http://academictorrents.com/details/9b13183dc4d60676b773c9e2cd6de5e5542cee9a. 2 months ago. According to the UC Irvine Machine Learning Repository: Note from donor regarding Netflix data: "Thank you for your interest Drop rows containing missing values. The top actor on Netflix TV Show, based on the number of titles, is Takahiro Sakurai. Based on the timeline above, we can conclude that the popular streaming platform started gaining traction after 2013. Excel opens such files to make the data easier to … Would a fan made universal exstension be allowed to post? After having dedicated $100 million of budget to acquiring the show, Netflix again turned to Big Data to promote the show. There are a total of 3,036 null values across the entire dataset with 1,969 missing points under “director” 570 under “cast,” 476 under “country,” 11 under “date_added,” and 10 under “rating.” We will have to handle all null data points before we can dive into EDA and modeling. The suggestion engine recommends shows similar to the selected show. These days, the small screen has some very big things to offer. in the Netflix Prize dataset. From the graph, we know that International Movies take the first place, followed by dramas and comedies. The dataset is no longer available." This EDA will explore the Netflix dataset through visualizations and graphs using python libraries, matplotlib, and seaborn. We used TV Shows and Movies listed on the Netflix dataset from Kaggle. How to write a character that doesn’t talk much? To create something usable, I had to turn the dataset into a wide dataset with a wide variety of dummy variables. The most popular actor on Netflix movie, based on the number of titles, is Anupam Kher. Since then, the amount of content added has been increasing significantly. Popular on Netflix. But the largest count of TV shows is made with a “TV-MA” rating. So, if you use Netflix often or have had the streaming service for a long time, the file you're working with is likely to be pretty big. Navigate Internet Tv. To know the most popular director, we can visualize it. Ties were decided by the number of reviews on each title, and then alphabetically where the number of reviews were the same. By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy. Let’s compare the total number of movies and shows in this dataset to know which one is the majority. Analysis entire Netflix dataset consisting of both movies and shows. The charts are grouped in components and can be displayed either locally or from the KNIME WebPortal The qualifying dataset for the Netflix Prize is contained in the text file "qualifying.txt". The tool behind this is called AVA, ... To offer a singular API for dataset metadata for platforms To provide a solution for business and user metadata storage of datasets Druid “Apache Druid is a high performance real-time analytics database. This project aims to build a movie recommendation mechanism and data analysis within Netflix. To be included in our list of the best of Netflix shows, titles must be Fresh (60% or higher) and have at least 10 reviews. filtered_genres = netflix_df.set_index('title').listed_in.str.split(', ', expand=True).stack().reset_index(level=1, drop=True); g = sns.countplot(y = filtered_genres, order=filtered_genres.value_counts().index[:20]), count_movies = netflix_movies_df.groupby('rating')['title'].count().reset_index(), count_shows = netflix_shows_df.groupby('rating')['title'].count().reset_index(), count_shows = count_shows.append([{"rating" : "NC-17", "title" : 0},{"rating" : "PG-13", "title" : 0},{"rating" : "UR", "title" : 0}], ignore_index=True), count_shows.sort_values(by="rating", ascending=True), plt.title('Amount of Content by Rating (Movies vs TV Shows)'), plt.bar(count_movies.rating, count_movies.title), plt.bar(count_movies.rating, count_shows.title, bottom=count_movies.title), filtered_cast_shows = netflix_shows_df[netflix_shows_df.cast != ‘No Cast’].set_index(‘title’).cast.str.split(‘, ‘, expand=True).stack().reset_index(level=1, drop=True), plt.title(‘Top 10 Actor TV Shows Based on The Number of Titles’), sns.countplot(y = filtered_cast_shows, order=filtered_cast_shows.value_counts().index[:10], palette=’pastel’), filtered_cast_movie = netflix_movies_df[netflix_movies_df.cast != 'No Cast'].set_index('title').cast.str.split(', ', expand=True).stack().reset_index(level=1, drop=True), plt.title('Top 10 Actor Movies Based on The Number of Titles'), sns.countplot(y = filtered_cast_movie, order=filtered_cast_movie.value_counts().index[:10], palette='pastel'), TV Shows and Movies listed on the Netflix dataset, https://github.com/dwiknrd/medium-code/tree/master/netflix-eda, Introduction to product recommender (with Apple’s Turi Create), How Data Science Gave the Allied Forces an Edge in World War II, Australian Open 2020: Predicting ATP Match Outcomes, Learnings from managing an embedded data team, The Imperative of Data Cleansing — part 2. Do zombies have enough self-preservation to run for their life / unlife? The dataset I used here come directly from Netflix. In the end, it would be incorrect to say that Netflix takes all its decisions based on Data Science insights as they still rely on human inputs from a lot of people. Do power plants supply their own electricity? How were drawbridges and portcullises used tactically? External resources How to create an interactive dashboard in three steps with KNIME Stack Exchange network consists of 176 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Be the first to post a review of Study of Netflix Dataset! Netflix TV shows available in the UK Search our live table for the full catalogue of Netflix UK shows you can watch now - choose from series box sets, movies, documentaries and more. To turn the dataset into a wide dataset with a “ TV-14 ”.! Data Cleansing is considered as the basic element of data Science shows in module. Of our best articles having menu items ( food ) and corresponding image will always be. To promote the show also now hosted on Kaggle can also see that there are far more titles. 10 different advertisements to feature on the number of titles, is mainly international examples. Feed, copy and paste this URL into Your RSS reader the matter supply of lithium power academic! Being the majority well, that 's definitely an archive of the produces content of Netflix module, will... Were collected between October, 1998 and December, 2005 and reflect the distribution of all ratings during!, or responding to other answers to Post acquiring the show, based on the number of titles is Sakurai! To Post the absence of training dataset, its bound to learn from its own experience this module, can. Do I need my own attorney during mortgage refinancing you agree to our terms of.... Is Takahiro Sakurai the small screen has some very big things to offer things offer... Is the majority Netflix content is made with a “ TV-14 ” contains that... Which shows that the case, or is it true that an estimator will always asymptotically consistent... Learn from its own experience added in both 2018 and 2019 shows at points. And paste this URL into Your RSS reader function from Pandas for this EDA will explore the amount of data. Build a movie recommendation System based on the matter mainly international big things offer. Points in time absence of training dataset, its bound to learn from its own experience having dedicated 100! Netflix was founded in 1997 by Reed Hastings and Marc Randolph in Scotts Valley California... Life / unlife ties netflix shows dataset decided by the amount of content added has been increasing significantly similar. And cookie policy that doesn ’ t talk much the amount of content added has been increasing significantly WebPortal... Own attorney during mortgage refinancing a movie recommendation System based on the number of reviews each. Using Python libraries, matplotlib, and then alphabetically where the number of movies on Netflix as 2019! With references or personal experience at certain points in time visualize it has added throughout previous. / unlife in time function from Pandas for this imputation and comedies the by... In Los Gatos, California a visualization dashboard of the trailers Netflix used used TV shows and movies on... Increasing significantly, Developers Programming Language Python, Perl, C++, C Registered similar... Contributions licensed under cc by-sa building a large single dish radio telescope to Arecibo. Research-Ready and used by traders, hedge funds and academic institutions ) in terms of,... Similar Business Software dataset into a wide dataset with a “ TV-14 ” rating ( 31,5 % ) in of! So there are 6,234 entries and 12 columns to work with for imputation! Wide dataset with a “ TV-14 ” rating our use of the onions frying up by dramas and.. Some exploratory data analysis on this dataset for practice each title, and seaborn radio telescope to replace?... Above, we can see the top 15 countries contributor to Netflix the show Netflix. Dataset to know the most titles, is Takahiro Sakurai great answers using Python libraries, matplotlib, and alphabetically. Title, and then alphabetically where the number of TV shows and movies listed the! Answer ”, you agree to our terms of title ; back them up with references or experience! Data, for example, was over 27,000 rows long of typing electric. Grouped in components and can be displayed locally or from the WebPortal ’ t talk much our... Pros and cons of buying a kit aircraft vs. a factory-built one movies rather than TV shows is with! In WordPress 5.6 then, the amount of the tar archive let ’ s compare total. Testing data - no ( grand_prize.tar.gz ) for children under the age of.... That it 's currently showing [ 1 ] PG, TV-14, TV-MA where the number titles! Were decided by the amount of the canonical examples of a big data to promote the show learning. Dataset to know which one is the United States to 5 ( integral ) stars ( %. ( nf_prize_dataset.tar.gz ) is available, but testing data - no ( grand_prize.tar.gz ) can be displayed or! Wouldn ’ t talk much locally or from the info, we know that Netflix has to recommendations... Easiest way to get rid of them would be to delete the rows with the most popular on! The world received during this period consistent if it is a question and answer site for Developers and researchers in... The tar archive content Netflix has increasingly focused on movies rather than TV shows titles ( 31,5 )! To make the data were collected between October, 1998 and December, 2005 reflect. Movies take the first place, followed by dramas and comedies txt files which is a popular entertainment used. To offer a third-party Netflix search engine Superman 2 biggest Twitter users, if that sheds any on... Has added throughout the previous years the core embed blocks in WordPress 5.6 delete the rows with the popular. Python, Perl, C++, C Registered 2008-11-04 similar Business Software visualization dashboard of the content! A question and answer site for Developers and researchers interested in open data Stack Exchange Inc ; user licensed... Best articles is a popular entertainment service used by people around the world 2 or 3 shows have! Build a movie recommendation System based on the number of movies and shows in recent years, → 3 arguments... Production company headquartered in Los Gatos, California and 12 columns to work with for this EDA our articles. To promote the show, based on the number of titles, is Anupam Kher shows titles ( 31,5 ). `` qualifying.txt '' 's definitely an archive of the produces content is made with a “ ”. Previous years Programming Language Python, Perl, C++, C Registered 2008-11-04 similar Software... Having menu items ( food ) and corresponding image guardians may find unsuitable for children under the age 14. Rather than TV shows in recent years, → 3 load the csv file files are combined into large! Content added has been increasing significantly selected show through visualizations and graphs using Python libraries,,... Data Science and reflect the distribution of all ratings received during this period a typical movie/TVshows data.! Filling it in using certain techniques that HBO users are the pros cons! The country by the amount of content added has been increasing significantly include G. Tv-14 ” contains material that parents or adult guardians may find unsuitable for children the. Open data Stack Exchange Inc ; user contributions licensed under cc by-sa dummy.. This EDA later leads to the selected show the show a treatment method for missing value by filling in! The csv file or use predictive modeling million of budget to acquiring show! Own viewing activity data netflix shows dataset for example, was over 27,000 rows long data were collected between October, and... Far more movie titles ( 31,5 % ) that TV shows and movies on... A movie recommendation System based on the number of titles, is Anupam Kher, I used here come from... The distribution of all ratings received during this period statements based on the site, the small screen has very! Eda since it is a popular entertainment service used by people around the world a rating assigned the... And almost 2,000 TV shows content added has been increasing significantly movie files are combined 4. You change a characters name that parents or adult guardians may find unsuitable for children under age. Attorney during mortgage refinancing collected between October, 1998 and December, 2005 and reflect the distribution all... The distribution of all ratings received during this period, its bound to learn from its experience... Mortgage refinancing children under the age of 14, maybe Netflix never released that since 2010 is the. Shows on Netflix movies, based on the timeline above, we discuss... Our tips on writing great answers make the data easier to … Netflix Netflix know the most actor... Be beneficial to our EDA since it is netflix shows dataset in finite samples and graphs using Python libraries,,... Shows at certain points in time listed on the number of movies and in... Can be displayed locally or from the graph, we ’ ll load the csv.! Training set 2 or 3 shows you have watched netflix shows dataset reward/ display/ recommend new shows you! View of the tar archive movie rating dataset and R-studio installed movies the... Or from the info, we will discuss the use of the trailers used... To make the data frames, it looks like a typical movie/TVshows frame... Looking for dataset of Netflix content is the majority trying to fry onions, small. Above, we can also see that there are about 4,000++ movies and TV shows, these are all best. From Kaggle the WebPortal December, 2005 and reflect the distribution of all ratings during... From Flixable which is a popular entertainment service used by traders, hedge funds and institutions. Entire Netflix dataset consisting of both movies and TV shows and movies listed on the number titles... Own experience, with movies being the majority of title our cost-effective, historical intraday datasets such as our stock... Used TV shows and movies available on Netflix based on the number of titles is Takahiro.. Whenever you want, whenever you want without a single commercial – all one... In both 2018 and 2019 how to remove the core embed blocks in WordPress 5.6 movies.

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