Question

#########################PANDAS LANGUAGE##################

#########################MATPLOT LIB#########################

# read movie.csv into a DataFrame called 'movie'
# describe the dataframe
#rename the column Runtime (Minutes) with Runtime_Minutes, and Revenue (Millions) with Revenue_Millions 

# show if any column has null value

# count total number of null vlaues in the dataframe

# print those rows which has null values

# fill null values, 

#if column is numerical than fill with means (if there is no numerical missing value in 

#data frame then don't code in this)

#if column is categorical than fill with most frequent value (if there is no categorical missing value in 

#data frame then don't code in this)

# plot histogram of the column name year in movie dataframe, which shows how many movies release in a year.

# print the movie detail with title 'Grumpier Old Men'.

# show those movies which are released after 1995-01-01

# sort the movie DataFrame in decending order based on release_date

# for each year, display the total number of movie with specific gerne for example Action=1000,adventure=400

# plot histogram the upper calculated total count

​# filter the movies with specific gerne # like show only those movies which are selected Action gerne 

# filter the movies with specific gerne

# like show only those movies which are selected Action gerne

# for each Director, display all the movies with detail.

​

# count the movies and plot barchart top 10 director's movies.

​# for each Actor, display all the movies with detail.

​# count the movies and visualize the top 10 actor's movies in plot

​

In [27]:

data file

Rank	Title	Genre	Description	Director	Actors	Year	Runtime (Minutes)	Rating	Votes	Revenue (Millions)	Metascore
1	Guardians of the Galaxy	Action,Adventure,Sci-Fi	A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.	James Gunn	Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana	2014	121	8.1	757074	333.13	76
2	Prometheus	Adventure,Mystery,Sci-Fi	Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.	Ridley Scott	Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron	2012	124	7	485820	126.46	65
3	Split	Horror,Thriller	Three girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.	M. Night Shyamalan	James McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula	2016	117	7.3	157606	138.12	62
4	Sing	Animation,Comedy,Family	In a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.	Christophe Lourdelet	Matthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson	2016	108	4.2	60545	270.32	59
5	Suicide Squad	Action,Adventure,Fantasy	A secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.	David Ayer	Will Smith, Jared Leto, Margot Robbie, Viola Davis	2015	123	3.2	393727	325.02	40
6	The Great Wall	Action,Adventure,Fantasy	European mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.	Yimou Zhang	Matt Damon, Tian Jing, Willem Dafoe, Andy Lau	2014	103	6.1	56036	45.13	42
7	La La Land	Comedy,Drama,Music	A jazz pianist falls for an aspiring actress in Los Angeles.	Damien Chazelle	Ryan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons	2013	128	5.3	258682	151.06	93
8	Mindhorn	Comedy	A has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.	Sean Foley	Essie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh	2010	89	6.4	2490		71

Answer 1

# import necessary library
import pandas as pd
import matplotlib.pyplot as plt

#  read movie.csv into a DataFrame called 'movie'
movie = pd.read_csv('movies.csv')

# describe the dataframe
movie.describe()

# rename the column Runtime (Minutes) with Runtime_Minutes, and Revenue (Millions) with Revenue_Millions 
movie.rename(columns = {'Runtime (Minutes)':'Runtime_Minutes','Revenue (Millions)':'Revenue_Millions'}, inplace = True)

# show if any column has null value
movie.columns[movie.isna().any()].tolist()

# count total number of null vlaues in the dataframe
movie.isna().sum().sum()

# print those rows which has null values
movie[movie.isna().any(axis=1)]

# Fill null values : if column is numerical than fill with means
# Here 'Revenue_Millions', 'Metascore' these two columns are having null values and both are numerical.
movie.fillna(movie.mean(), inplace=True)

# plot histogram of the column name year in movie dataframe, which shows how many movies release in a year.
fig, ax = plt.subplots(figsize =(8, 6))
movie['Year'].hist()
fig.show()

# print the movie detail with title 'Grumpier Old Men'.
movie[movie.Title=='Grumpier Old Men']
# It seems there is no record with this title.

# show those movies which are released after 1995-01-01
movie[movie.Year>1995]

# sort the movie DataFrame in decending order based on release_date
movie.sort_values('Year', ascending=False)

# for each year, display the total number of movie with specific gerne for example
count = movie.groupby('Genre')['Genre'].count()
print(count)

#plot histogram the upper calculated total count
fig, ax = plt.subplots(figsize =(10, 7))
fig = count.hist()
plt.show()

# filter the movies with specific gerne # like show only those movies which are selected Action gerne
movie[movie['Genre']=='Action']

# for each Director, display all the movies with detail.
list_director = movie['Director'].unique().tolist()
for director in list_director:
    df = movie[movie['Director'] == director]
    print('---------------------------------'+director+'---------------------------------------')
    print(df.head())


# count the movies and plot barchart top 10 director's movies.
top_10_directors = movie.groupby('Director')['Director'].count().sort_values(ascending=False).head(10)
print(top_10_directors)


fig, ax = plt.subplots(figsize =(8, 6))
top_10_directors.plot.bar()
plt.show()

# for each Actor, display all the movies with detail.
import itertools
list_actor = movie['Actors'].unique().tolist()
l=[]
for actor in list_actor:
    l.append(actor.split(','))
list_flat = set(itertools.chain(*l))
#print(list_flat)
for actor in list_flat:
    df = movie[movie['Actors'].str.contains(actor)]
    print('---------------------------------'+actor+'---------------------------------------')
    print(df.head())



# count the movies and visualize the top 10 actor's movies in plot
actor_list = []
count_list = []
for actor in list_flat:
    length = movie[movie['Actors'].str.contains(actor)].shape[0]
    actor_list.append(actor)
    count_list.append(length)
actor_dict = {'Actor':actor_list, 'Count':count_list}

actor_df = pd.DataFrame.from_dict(actor_dict)
fig, ax = plt.subplots(figsize =(8, 6))
actor_df.sort_values('Count', ascending=False).head(10).plot.bar(x='Actor',y='Count')
fig.show()

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