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 :