Data_Analysis_Using_Python_Libraries_Series

This Repo contains various Data Analysis on different Kaggle datasets and providing insights into the dataset by making use of Python libraries.

1> Facebook Data Analytics

1️⃣ Dataset :

https://www.kaggle.com/sheenabatra/facebook-data 🔗

2️⃣ Processes Involved :

->Data Preparation and Cleaning

->Exploratory Analysis and Visualization

->Questions and Answers

->Inferences and Conclusion

3️⃣ Libraries Used :

->opendatasets - It is a Python library for downloading datasets from online sources like Kaggle and Google Drive.

->numpy

->pandas

->matplotlib

4️⃣ Google Collab Notebook File :

Navigate to the Below Link: 👇

https://github.com/ManikantaSanjay/Data_Analysis_Using_Python_Libraries_Series/blob/main/Facebook_Data_Analysis.ipynb 🔗

Click on Open in Collab at the top and fork it.

2> Data Analytics On Zomato Restaurants

1️⃣ Content in Dataset :

• Restaurant Id
• Restaurant Name
• Country Code
• City
• Address
• Locality
• Locality Verbose
• Longitude
• Latitude
• Cuisines
• Average Cost for two
• Currency
• Has Table booking
• Has Online delivery
• Is delivering
• Switch to order menu
• Price Range
• Aggregate Rating
• Rating color
• Rating text
• Votes

2️⃣ Downloading the Dataset :

By making use of the opendatasets library we download the dataset required for our EDA(Exploratory Data Analysis)

Dataset URL : https://www.kaggle.com/shrutimehta/zomato-restaurants-data 🔗

3️⃣ Importing Dataset :

By making use of the pandas library we import the dataset into a pandas dataframe.

4️⃣ Exploratory Analysis and Visualization :

It deals with the following aspects :

-> Understanding the Geographical Spread

-> Understanding the Rating Aggregate, Color and Text

-> Understanding the Country and their Respective Currency

-> Understanding the Online Delivery Distribution

-> Understanding the Coverage of the City

5️⃣ Asking and Answering Questions :

After understanding the several insights about the restaurants present in the survey, we try to answer them using data frame operations and visualizations.

We ask the following questions:

Q1: From which Locality Maximum hotels are listed in Zomato ?

Q2: What kind of Cuisine these highly rates restaurants offer ?

Q3: How many of such restaurants accept online delivery ?

Q4: Understanding the Restaurants Rating locality wise ?

Q5: Understanding the Relation between Rating VS Cost of Dining ?

Q6: Location of Highly Rated restaurants across New Delhi ?

Q7: Understanding about Common Eateries ?

6️⃣ Inferences and Conclusions :

We've drawn many inferences from the survey and we discuss them in this part of the project.

7️⃣ Steps to Use :

Navigate to the Below Link: 👇

https://github.com/ManikantaSanjay/Data_Analysis_Using_Python_Libraries_Series/blob/main/Data_Analysis_on_Restaurants_Listed_In_Zomato.ipynb 🔗

Click on Open in Collab at the top and fork it.

Add a star 🌟 to the repo if u like it.:smiley: Thank You :v: