In [11]:
plt.figure(figsize = (6, 6))
sns.heatmap(ntfx_df.isnull())
Out[11]:
<AxesSubplot:>
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
filepath = "C:\\Users\\abdelilah\\Desktop\\Python Projects\\Netflix\\"
ntfx_df = pd.read_csv(filepath + "Netflix Dataset.csv", delimiter = ",")
ntfx_df
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | s1 | TV Show | 3% | NaN | João Miguel, Bianca Comparato, Michel Gomes, R... | Brazil | August 14, 2020 | TV-MA | 4 Seasons | International TV Shows, TV Dramas, TV Sci-Fi &... | In a future where the elite inhabit an island ... |
| 1 | s2 | Movie | 07:19 | Jorge Michel Grau | Demián Bichir, Héctor Bonilla, Oscar Serrano, ... | Mexico | December 23, 2016 | TV-MA | 93 min | Dramas, International Movies | After a devastating earthquake hits Mexico Cit... |
| 2 | s3 | Movie | 23:59 | Gilbert Chan | Tedd Chan, Stella Chung, Henley Hii, Lawrence ... | Singapore | December 20, 2018 | R | 78 min | Horror Movies, International Movies | When an army recruit is found dead, his fellow... |
| 3 | s4 | Movie | 9 | Shane Acker | Elijah Wood, John C. Reilly, Jennifer Connelly... | United States | November 16, 2017 | PG-13 | 80 min | Action & Adventure, Independent Movies, Sci-Fi... | In a postapocalyptic world, rag-doll robots hi... |
| 4 | s5 | Movie | 21 | Robert Luketic | Jim Sturgess, Kevin Spacey, Kate Bosworth, Aar... | United States | January 1, 2020 | PG-13 | 123 min | Dramas | A brilliant group of students become card-coun... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 7784 | s7783 | Movie | Zozo | Josef Fares | Imad Creidi, Antoinette Turk, Elias Gergi, Car... | Sweden, Czech Republic, United Kingdom, Denmar... | October 19, 2020 | TV-MA | 99 min | Dramas, International Movies | When Lebanon's Civil War deprives Zozo of his ... |
| 7785 | s7784 | Movie | Zubaan | Mozez Singh | Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan... | India | March 2, 2019 | TV-14 | 111 min | Dramas, International Movies, Music & Musicals | A scrappy but poor boy worms his way into a ty... |
| 7786 | s7785 | Movie | Zulu Man in Japan | NaN | Nasty C | NaN | September 25, 2020 | TV-MA | 44 min | Documentaries, International Movies, Music & M... | In this documentary, South African rapper Nast... |
| 7787 | s7786 | TV Show | Zumbo's Just Desserts | NaN | Adriano Zumbo, Rachel Khoo | Australia | October 31, 2020 | TV-PG | 1 Season | International TV Shows, Reality TV | Dessert wizard Adriano Zumbo looks for the nex... |
| 7788 | s7787 | Movie | ZZ TOP: THAT LITTLE OL' BAND FROM TEXAS | Sam Dunn | NaN | United Kingdom, Canada, United States | March 1, 2020 | TV-MA | 90 min | Documentaries, Music & Musicals | This documentary delves into the mystique behi... |
7789 rows × 11 columns
ntfx_df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 7789 entries, 0 to 7788 Data columns (total 11 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Show_Id 7789 non-null object 1 Category 7789 non-null object 2 Title 7789 non-null object 3 Director 5401 non-null object 4 Cast 7071 non-null object 5 Country 7282 non-null object 6 Release_Date 7779 non-null object 7 Rating 7782 non-null object 8 Duration 7789 non-null object 9 Type 7789 non-null object 10 Description 7789 non-null object dtypes: object(11) memory usage: 669.5+ KB
FIRST STEP: Is there any Duplicate Record in this dataset ? If yes, then remove the duplicate records.
duplics = ntfx_df[ntfx_df.duplicated()]
duplics
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 6300 | s684 | Movie | Backfire | Dave Patten | Black Deniro, Byron "Squally" Vinson, Dominic ... | United States | April 5, 2019 | TV-MA | 97 min | Dramas, Independent Movies, Thrillers | When two would-be robbers accidentally kill a ... |
| 6622 | s6621 | Movie | The Lost Okoroshi | Abba T. Makama | Seun Ajayi, Judith Audu, Tope Tedela, Ifu Enna... | Nigeria | September 4, 2020 | TV-MA | 94 min | Comedies, Dramas, Independent Movies | A disillusioned security guard transforms into... |
# I tried the duplicated() method to see if there's any duplicates but as it looks it prompted two rows that don't seem to be
# the same, in fact the only thing they have in common is the "Rating", so i'd say there's no duplicates and move on
SECOND STEP: Is there any Null Value present in any column ? Show with Heat-map.
plt.figure(figsize = (6, 6))
sns.heatmap(ntfx_df.isnull())
<AxesSubplot:>
# yeah it seems like there's a few missing values, specifically in the 3rd, 4th, 5th and 6th rows
First Task: For 'House of Cards', what is the Show Id and Who is the Director of this show ?
print("ID of the show is: ",list(ntfx_df.loc[ntfx_df["Title"].eq('House of Cards'), 'Show_Id'])[0])
print("Directors of the show are: ",list(ntfx_df.loc[ntfx_df["Title"].eq('House of Cards'), 'Director'])[0])
ID of the show is: s2833 Directors of the show are: Robin Wright, David Fincher, Gerald McRaney, John David Coles, David Manson
Second Task: In which year the highest number of the TV Shows & Movies were released ? Show with Bar Graph.
ntfx_df["Release_Date"] = pd.to_datetime(ntfx_df["Release_Date"])
sorted(pd.DatetimeIndex(ntfx_df["Release_Date"]).year.value_counts().index)
[2008.0, 2009.0, 2010.0, 2011.0, 2012.0, 2013.0, 2014.0, 2015.0, 2016.0, 2017.0, 2018.0, 2019.0, 2020.0, 2021.0]
plt.figure(figsize = (15, 7))
sns.countplot(x = (pd.DatetimeIndex(ntfx_df["Release_Date"]).year),
hue = ntfx_df["Category"])
plt.title("Production of Movies and TV Shows 2008-2021",
fontdict = {'fontsize' : 12,
'fontweight' : 'bold'})
plt.xlabel("Years",
fontdict = {'fontsize' : 9,
'fontweight' : 'bold'})
plt.ylabel("Count of each Category",
fontdict = {'fontsize' : 9,
'fontweight' : 'bold'})
Text(0, 0.5, 'Count of each Category')
# So i'd say based on the graph the highest amount of movies and tv shows recorded was in 2019
Third Task: How many Movies & TV Shows are in the dataset ? Show with Bar Graph.
plt.figure(figsize = (10, 7))
sns.countplot(x = ntfx_df["Category"],
hue = ntfx_df["Category"])
plt.title("Movies and TV Shows",
fontdict = {'fontsize' : 12,
'fontweight' : 'bold'})
plt.xlabel("Category",
fontdict = {'fontsize' : 9,
'fontweight' : 'bold'})
plt.ylabel("Count of each Category",
fontdict = {'fontsize' : 9,
'fontweight' : 'bold'})
Text(0, 0.5, 'Count of each Category')
#next time i should learn how to add labels indicating how many are there in each category
Fourth Task: Show all the Movies that were released in year 2000.
ntfx_df[(ntfx_df["Category"] == "Movie") & (pd.DatetimeIndex(ntfx_df["Release_Date"]).year == 2000)]
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description |
|---|
# this dataset doesn't have any data that goes back to 2000, the farthest one is from 2008, so i'll just bring data from 2010
ntfx_df[(ntfx_df["Category"] == "Movie") & (pd.DatetimeIndex(ntfx_df["Release_Date"]).year == 2010)]
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3840 | s3841 | Movie | Mad Ron's Prevues from Hell | Jim Monaco | Nick Pawlow, Jordu Schell, Jay Kushwara, Micha... | United States | 2010-11-01 | NR | 84 min | Cult Movies, Horror Movies | This collection cherry-picks trailers, forgott... |
Fifth Task: Show only the Titles of all TV Shows that were released in India only.
ntfx_df[(ntfx_df["Category"] == "TV Show") & (ntfx_df["Country"] == "India")]
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 86 | s87 | TV Show | 21 Sarfarosh: Saragarhi 1897 | NaN | Luke Kenny, Mohit Raina, Mukul Dev | India | 2018-12-01 | TV-14 | 1 Season | International TV Shows, TV Dramas | In one of history's greatest last stands, a ba... |
| 132 | s133 | TV Show | 7 (Seven) | Nizar Shafi | Rahman, Havish, Regina Cassandra, Nandita Swet... | India | 2019-07-30 | TV-14 | 1 Season | TV Shows | Multiple women report their husbands as missin... |
| 340 | s341 | TV Show | Agent Raghav | NaN | Sharad Kelkar, Aahana Kumra, Mahesh Manjrekar,... | India | 2017-04-15 | TV-14 | 1 Season | Crime TV Shows, International TV Shows, TV Act... | A mix of brilliance, erudition and skill enabl... |
| 364 | s365 | TV Show | Akbar Birbal | NaN | Kiku Sharda, Vishal Kotian, Delnaaz Irani | India | 2020-03-31 | TV-G | 1 Season | Kids' TV, TV Comedies, TV Dramas | From battles of wit to fights for justice, Emp... |
| 533 | s534 | TV Show | Anjaan: Rural Myths | NaN | NaN | India | 2018-12-15 | TV-14 | 1 Season | International TV Shows, TV Horror, TV Thrillers | Spine-chilling stories of malevolent spirits u... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 6249 | s6249 | TV Show | The Creative Indians | NaN | NaN | India | 2020-08-24 | TV-MA | 2 Seasons | Docuseries, International TV Shows | From chefs and comedians to filmmakers and fas... |
| 6400 | s6399 | TV Show | The Golden Years with Javed Akhtar | NaN | NaN | India | 2017-06-01 | TV-G | 1 Season | Docuseries, International TV Shows | Writer, poet and lyricist Javed Akhtar hosts t... |
| 6469 | s6468 | TV Show | The House That Made Me | NaN | Vinay Pathak | India | 2017-03-31 | TV-PG | 3 Seasons | International TV Shows, Reality TV | With host Vinay Pathak, Indian celebrities ret... |
| 7294 | s7293 | TV Show | Typewriter | NaN | Aarna Sharma, Aaryansh Malviya, Mikail Gandhi,... | India | 2019-07-19 | TV-MA | 1 Season | International TV Shows, TV Horror, TV Mysteries | Three young friends in Goa plan to search an o... |
| 7705 | s7704 | TV Show | Yeh Meri Family | NaN | Vishesh Bansal, Mona Singh, Akarsh Khurana, Ah... | India | 2018-08-31 | TV-PG | 1 Season | International TV Shows, TV Comedies | In the summer of 1998, middle child Harshu bal... |
71 rows × 11 columns
directors = pd.DataFrame(columns = ["Director Name", "Production Count"])
directors["Director Name"] = ntfx_df["Director"].value_counts().index
directors["Production Count"] = list(ntfx_df["Director"].value_counts())
directors.head(10)
| Director Name | Production Count | |
|---|---|---|
| 0 | Raúl Campos, Jan Suter | 18 |
| 1 | Marcus Raboy | 16 |
| 2 | Jay Karas | 14 |
| 3 | Cathy Garcia-Molina | 13 |
| 4 | Youssef Chahine | 12 |
| 5 | Martin Scorsese | 12 |
| 6 | Jay Chapman | 12 |
| 7 | Steven Spielberg | 10 |
| 8 | David Dhawan | 9 |
| 9 | Robert Rodriguez | 8 |
Seventh Task: Show all the Records, where "Category is Movie and Type is Comedies" or "Country is United Kingdom".
ntfx_df["Type"].value_counts()
Documentaries 334
Stand-Up Comedy 321
Dramas, International Movies 320
Comedies, Dramas, International Movies 243
Dramas, Independent Movies, International Movies 215
...
Romantic TV Shows, TV Action & Adventure, TV Dramas 1
TV Action & Adventure, TV Dramas, Teen TV Shows 1
Action & Adventure, Cult Movies 1
Action & Adventure, Faith & Spirituality, Sci-Fi & Fantasy 1
Horror Movies, International Movies, Sci-Fi & Fantasy 1
Name: Type, Length: 492, dtype: int64
filter_mcuk = ntfx_df[(ntfx_df["Category"] == "Movie") & (ntfx_df["Country"] == "United Kingdom")]
filter_mcuk = filter_mcuk[filter_mcuk["Type"].str.contains("Comedy|Comedies")]
Eight Task: In how many movies/shows, Tom Cruise was cast ?
ntfx_df[ntfx_df["Cast"].str.contains("Tom Cruise", na = False)]
| Show_Id | Category | Title | Director | Cast | Country | Release_Date | Rating | Duration | Type | Description | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 3860 | s3861 | Movie | Magnolia | Paul Thomas Anderson | Jeremy Blackman, Tom Cruise, Melinda Dillon, A... | United States | 2020-01-01 | R | 189 min | Dramas, Independent Movies | Through chance, human action, past history and... |
| 5071 | s5071 | Movie | Rain Man | Barry Levinson | Dustin Hoffman, Tom Cruise, Valeria Golino, Ge... | United States | 2019-07-01 | R | 134 min | Classic Movies, Dramas | A fast-talking yuppie is forced to slow down w... |
Ninth Task: What are the different Ratings defined by Netflix ?
ntfx_df["Rating"].unique()
array(['TV-MA', 'R', 'PG-13', 'TV-14', 'TV-PG', 'NR', 'TV-G', 'TV-Y', nan,
'TV-Y7', 'PG', 'G', 'NC-17', 'TV-Y7-FV', 'UR'], dtype=object)
9.1. How many Movies got the 'TV-14' rating, in Canada ?
len(ntfx_df[(ntfx_df["Rating"] == "TV-14") & (ntfx_df["Country"] == "Canada")].index)
23
9.2. How many TV Shows got the 'R' rating, after year 2018 ?
len(ntfx_df[(ntfx_df["Rating"] == "R") & (pd.DatetimeIndex(ntfx_df["Release_Date"]).year > 2018)].index)
450
Tenth Task: What is the maximum duration of a Movie/Show on Netflix ?
movies = ntfx_df[ntfx_df["Category"] == "Movie"]
shows = ntfx_df[ntfx_df["Category"] == "TV Show"]
print("Longest Movie is {} minutes".format(pd.to_numeric(movies["Duration"].str.strip(" min")).max()))
Longest Movie is 312 minutes
print("Longest Show is {} Seasons".format(pd.to_numeric(shows["Duration"].str.strip(" Seasons")).max()))
Longest Show is 16 Seasons
Eleventh Task: Which individual country has the Highest No. of TV Shows ?
print("{} has the highest No. of TV Shows".format(shows["Country"].value_counts().index[0]))
United States has the highest No. of TV Shows
Twelfth Task: How can we sort the dataset by Year ?
srt_idx = list(pd.DatetimeIndex(ntfx_df["Release_Date"]).year.argsort(axis = 0))
sorted_df = ntfx_df.reindex(srt_idx)
Thirteenth Task: Find all the instances where: Category is 'Movie' and Type is 'Dramas' or Category is 'TV Show' & Type is 'Kids' TV'.
filter_mdtk = ntfx_df[((ntfx_df["Category"] == "Movie") & (ntfx_df["Type"].str.contains("Drama|Dramas"))) |
((ntfx_df["Category"] == "TV Show") & (ntfx_df["Type"].str.contains("Kids")))]