Name: Capstone Project 1 PLAY STORE APP REVIEW ANALYSIS By- Kalyani Motkari
Uploaded: 2022-02-24
Duration: 6 min 40 s
Description: Capstone Project 1 PLAY STORE APP REVIEW ANALYSIS By- Kalyani Motkari.

Capstone Project 1 PLAY STORE APP REVIEW ANALYSIS By- Kalyani Motkari. 

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Capstone Project 1 PLAY STORE APP REVIEW ANALYSIS By- Kalyani Motkari

Review Play Store App : 1. Defining Problem Statement 2. Examining the Dataset 3. Preparing the Dataset 4. Attributes in Google Play store and User reviews 5. Exploratory data Analysis(EDA) a. Category wise Analysis b. Free vs Paid Apps c. The Highest Earning App d. User Review Analysis 6. Conclusion. 

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Review Play Store App :          1. Defining Problem Statement 2. Examining the Dataset 3. Preparing the Dataset  4. Attributes in Google Play store and User reviews 5. Exploratory data Analysis(EDA)       a. Category wise Analysis       b. Free vs Paid Apps       c. The Highest Earning App       d. User Review Analysis 6. Conclusion

Google Play. Google Play is an online store where people go to find their favorite apps, games, movies, TV shows, books, and more . It provides 2 million apps and games to billions of people around the world, generating over $120 billion in earnings for developers to date.. 

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Google Play is  an online store where people go to find their favorite apps, games, movies, TV shows, books, and more . It provides 2 million apps and games to billions of people around the world, generating over $120 billion in earnings for developers to date.

Problem Statement. Play store is a marketplace (App) for downloading Android applications for smartphones. Smartphones sells increasing YoY across world. Its very lucrative market for App developers as users are looking for comfort and their needs increasing like entertainment, games etc. It's important to find out what type of apps people downloading before developing an App for users and list that APP on Play Store for downloading. How does Size, Price and Type of app impacts the Rating’s and Sentiment of apps?. 

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Play store is a marketplace (App) for downloading Android applications for smartphones. Smartphones sells increasing YoY across world. Its very lucrative market for App developers as users are looking for comfort and their needs increasing like entertainment, games etc.  It's important to find out what type of apps people downloading before developing an App for users and list that APP on Play Store for downloading. How does Size, Price and Type of app impacts the Rating’s and Sentiment of apps?

1 . Play Store Data.csv: Contains all the details of the applications on Google Play store. There are 13 attributes that describe a given app. It has 9659 unique apps 2. User Review.csv: :This .csv file includes 3 attributes Sentiment , Sentiment Polarity and Sentiment Subjectivity .. 

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1 . Play Store Data.csv:  Contains all the details of the applications on Google Play store. There are 13 attributes that describe a given app. It has 9659 unique apps  2. User Review.csv:  :This .csv file includes 3 attributes Sentiment , Sentiment Polarity and Sentiment Subjectivity .

Preparing The Dataset : Loading the data sets: We have two different data sets, one is play store app data and the second data set with reviews of users of the apps We import various Python inbuilt libraries - NumPy, Pandas, present in columns Import Libraries: Matplotlib and Seaborn to work on the dataset. Data cleaning: Null values, Finding and removing Outliers, Removing duplicate and identical data. Data Imputation: Filling the missing categorical values with mode and numerical values with median. Conversion of price, installs, reviews into numerical values. Exploratory Data Analysis: Analyzing the data sets to summarize their main characteristics using statistical graphics and data visualizations method.. 

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Preparing The Dataset : Loading the data sets:  We have two different data sets, one is play store app data and the second data set with reviews of users of the apps We import various Python inbuilt libraries - NumPy, Pandas, present in columns Import Libraries:  Matplotlib and Seaborn to work on the dataset.  Data cleaning:  Null values, Finding and removing Outliers, Removing duplicate and identical data. Data Imputation:  Filling the missing categorical values with mode and numerical values with median. Conversion of price, installs, reviews into numerical values.   Exploratory Data Analysis:  Analyzing the data sets to summarize their main characteristics using statistical graphics and data visualizations method.

Data Preparation -
Refining Raw Data into Value

Attributes in Google Play store Data. 1.App - Application name 2.Category - Category the app belongs to 3.Rating - Overall user rating of the app 4 . Reviews - Number of user reviews for the app 5.Size - Size of the app 6.Installs - Number of user downloads for the app 7.Type - Paid or Free 8.Price - Price of the app 9.Content Rating - Suitable age group for given app 10.Genres - An App can belong to multiple genres 11.Last Updated- Date of Last modification by app development team 12.Current Ver- It shows Current version of app 13.Android Ver- It tells the app can run on which Android version compatible. 

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1.App - Application name  2.Category - Category the app belongs to  3.Rating - Overall user rating of the app  4 . Reviews - Number of user reviews for the app  5.Size - Size of the app  6.Installs - Number of user downloads for the app  7.Type - Paid or Free  8.Price - Price of the app  9.Content Rating - Suitable age group for given app        10.Genres - An App can belong to multiple genres       11.Last Updated-  Date of Last modification by app development team       12.Current Ver-  It shows Current version of app       13.Android Ver-  It tells the app can run on which Android version compatible

Attributes in User reviews. 1.App- Application name 2.Translated Review- User review 3.Sentiment- Positive/Negative/Neutral 4.Sentiment Polarity- Sentiment polarity score 5.Sentiment Subjectivity- Sentiment subjectivity score. 

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1.App-  Application name 2.Translated Review-  User review  3.Sentiment-  Positive/Negative/Neutral 4.Sentiment Polarity-  Sentiment polarity score  5.Sentiment Subjectivity-  Sentiment subjectivity score

Exploratory data Analysis(EDA) Co-Relation in Merged Data frames. 

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Exploratory data Analysis(EDA) Co-Relation in Merged  Data frames

Reviews
Installs
Sentiment_Polarity
Sentiment_subjectivity

We Examine Heatmap correlation and as we can not find any correlations between the different columns.

Exploratory data Analysis(EDA) Category wise Rating. 

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Exploratory data Analysis(EDA) Category wise Rating

Rating
COMMUNICATION
HEALTH AND FIT N _ ,
MAPS AND NAVIGATION

Analysis by Rating  1.Highest Ratings apps: Events, Art and Design, Education Categories has got 4 and above ratings. 2. Lowest Ratings apps: Dating, Maps and navigation, Video players category has got lowest ratings i.e. below 4.

Exploratory data Analysis(EDA ) Category wise Pricing. 

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Exploratory data Analysis(EDA ) Category wise Pricing

ART AND DESIG'
COMMUNICATI.or
FOOD AND
HEALTH AND FITN:-;
MAPS AND

As we can see that  Finance, Lifestyle and Medical  Category has got the highest pricing.

Exploratory data Analysis(EDA) Category wise Reviews. 

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Exploratory data Analysis(EDA) Category wise Reviews

Reviews
o
o
o
o
o
o
ART AND DESIGN
AUTO AND VEHICLES
BEAUTY
BOOKS AND REFERENCE
BUSINESS
COMICS
COMMUNICATION
DATING
EDUCATION
ENTERTAINMENT
EVENTS
FAMILY
FINANCE
FOOD AND DRINK
- GAME
HEALTH AND FITNESS
HOUSE HOME
LIBRARIES-AND-DEMO
LIFESTYLE
MAPS AND NAVIGATION
MEDICAL
NEWS AND MAGAZINES
PARENTING
PERSONALIZATION
PHOTOGRAPHY
PRODUCTIVITY
SHOPPING
SOCIAL
SPORTS
TOOLS
TRAVEL AND LOCAL
VIDÉO PLAYERS
WEATHER

The  Social, Communication and Game  category got the highest reviews.

Exploratory data Analysis(EDA) Count of Application in each category. 

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Exploratory data Analysis(EDA)   Count of Application in each category

Family and Game  apps have the highest market prevalence. Surprisingly  Tools, Business and Medical  apps are also at the Top  Count of applications.

Free vs Paid Applications. We Observed that 92.19% of Apps are free and only 7.81% of Apps are paid in Play store.. 

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We Observed that  92.19% of Apps are free  and only  7.81% of Apps are paid  in Play store.

Top 10 Expensive Application in Play Store. Top expaøve t&tbutlon I am 'ich I am ddl (host expensive app' I Am Rich Pro I am rich(premjurn rnost expensive •pp (H) I'm Rich - Trump Ed18m am Rlch has RICH mus Apps. 

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Top 10 Expensive Application in Play Store

Top expaøve t&tbutlon
I am 'ich
I am ddl (host expensive app'
I Am Rich Pro
I am rich(premjurn
rnost expensive •pp (H)
I'm Rich - Trump Ed18m
am Rlch has
RICH mus
Apps

I am rich  is the most expensive Application in the google play store.

Top 30 Genres Play Store Data. Total Count Tools Entertainment Education Business Medical Personalization Productivity Lifestyle Finance Sports Communication Action Health & Fitness m" o tog raphy News & Magazines Books & Reference Travel & Local Shopping Simulation Arcade Dating Casual Players & Editors Maps & Navigation Puzzle & Drink Role Playing Strategy Racing. 

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Total
Count
Tools
Entertainment
Education
Business
Medical
Personalization
Productivity
Lifestyle
Finance
Sports
Communication
Action
Health & Fitness
m" o tog raphy
News & Magazines
Books & Reference
Travel & Local
Shopping
Simulation
Arcade
Dating
Casual
Players & Editors
Maps & Navigation
Puzzle
& Drink
Role Playing
Strategy
Racing

The highest number of apps are from  Tools  genre. Tools, Entertainment, Education, Business  and  Medical  are top Genres for App.

Distribution of Size and Rating. Size Vs Rating 5.0 4.5 4.0 3.5 3.0 a: 2.5 2.0 1.5 1.0 20 40 60 80 Type Free Paid 100 Size. 

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Size Vs Rating
5.0
4.5
4.0
3.5
3.0
a:
2.5
2.0
1.5
1.0
20
40
60
80
Type
Free
Paid
100
Size

Large number of apps are in small size. 92.19%  apps are Free on Play Store. 8746  Apps are below of 50MB in size. 8786   Apps have rating more than 3.5 including Free and Paid.

Relationship viz Price and Rating. 8905 Apps are Free in type. The mean rating of Free apps is 4.18. 754 Apps are Paid in type. The mean rating of Paid apps Is 4.26. 

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8905  Apps are  Free  in type. The  mean  rating of  Free  apps is  4.18. 754  Apps are  Paid  in type. The  mean  rating of  Paid  apps Is  4.26

Relationship viz Reviews and Rating. Reviews Vs Rating 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.0 0.0 0.2 0.4 0.6 Reviews 0.8 1.0 le6. 

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Reviews Vs Rating
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.0
0.0
0.2
0.4
0.6
Reviews
0.8
1.0
le6

Vi z for Apps with less than 1000000 Reviews

9309  Apps have  less than  and  equal  to  1000000  reviews count. Rating’s of an  increasing slightly  as more people giving Reviews.

Overall Sentiment Count. The number of Unique Apps from Play store and User reviews merged dataset are 816. From Sentiment column , 64% are Positive, 22% are Negative and 13% are Neutral values.. 

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The number of  Unique  Apps from Play store and User reviews merged dataset are  816. From Sentiment column , 64%  are  Positive, 22%  are  Negative  and  13%  are  Neutral  values.

Categorywise Sentiment Count. Count 9 GAME FAMILY HEALTH AND FITNESS SPORTS TRAVEL AND LOCAL PRODUCTIVITY MEDICAL FINANCE TOOLS PHOTOGRAPHY PERSONALIZATION BUSINESS COMMUNICATION NEWS AND MAGAZINES LIFESTYLE SHOPPING ENTERTAINMENT FOOD AND DRINK BOOKS AND REFERENCE SOCIAL EDUCATION HOUSE AND HOME LIBRARIES AND DEMO AUTO AND VEHICLES ART AND DESIGN VIDEO PLAYERS BEAUTY PARENTING WEATHER MAPS AND NAVIGATION EVENTS COMICS. 

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Count
9
GAME
FAMILY
HEALTH AND FITNESS
SPORTS
TRAVEL AND LOCAL
PRODUCTIVITY
MEDICAL
FINANCE
TOOLS
PHOTOGRAPHY
PERSONALIZATION
BUSINESS
COMMUNICATION
NEWS AND MAGAZINES
LIFESTYLE
SHOPPING
ENTERTAINMENT
FOOD AND DRINK
BOOKS AND REFERENCE
SOCIAL
EDUCATION
HOUSE AND HOME
LIBRARIES AND DEMO
AUTO AND VEHICLES
ART AND DESIGN
VIDEO PLAYERS
BEAUTY
PARENTING
WEATHER
MAPS AND NAVIGATION
EVENTS
COMICS

The total number of Categories are  33. Game  category   has highest  Positive (2955)  and  Negative (1809)  sentiment count. Family  category has highest  Neutral (367)  sentiment count.

Sentiment Polarity Distribution. Positive: 22748 Negative: 07942 Neutral: 04823. 

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Positive:    22748 Negative:  07942 Neutral:     04823

Positive:   325 Negative:  63 Neutral:     28

Sentiment Polarity Vs Rating’s. Sentiment Polarity VS Rating 5.0 4.0 3.5 3.0 2.5 -1.00 -0.75 -0.50 -0.25 0.00 Sentiment Polarity 025 0.50 0.75 1.00. 

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Sentiment Polarity VS Rating
5.0
4.0
3.5
3.0
2.5
-1.00
-0.75
-0.50
-0.25
0.00
Sentiment Polarity
025
0.50
0.75
1.00

Sentiment Polarity vs Rating plot shows us, There is a  slightly increasing of polarity  as Rating of apps increases.

Top 10 Apps Positive Sentiment Count. Count 0 0 Helix Jump Duolingo: Leam Languages Free Calorie Counter - Macros Bowmasters Calorie Counter - MyFitnessPal 10 Best Foods for You Google Photos Bfit Workouts & Meal Planner Garena Free Fire DRAGON BALL LEGENDS 0 0. 

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Count
0
0
Helix Jump
Duolingo: Leam Languages Free
Calorie Counter - Macros
Bowmasters
Calorie Counter - MyFitnessPal
10 Best Foods for You
Google Photos
Bfit Workouts & Meal Planner
Garena Free Fire
DRAGON BALL LEGENDS
0
0

Helix Jump  is a App from merged dataset has highest  209 Positive  sentiment count.