Project Name - Capstone-Project-1-_-AirBnBb-Bookings-Analysis
Project Type - EDA
Contribution - Individual
Presented By - Sampreet Chakraborty
Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.
Here are six key steps that you can follow to conduct EDA:
Observe your dataset.
Find any missing values.
Categorize your values.
Find the shape of your dataset.
Identify relationships in your dataset.
Locate any outliers in your dataset.
Organizing a dataset.
Understanding variables.
Project Summary -
Airbnb, as in “Air Bed and Breakfast”, is a service that allows property owners to rent out their spaces/condos to travelers looking for a place to stay.
Airbnb was started in 2008 by Brian Chesky & Joe Gebbia, based in San Francisco, California. The platform is accessible via website and mobile app.
Since 2008, guests and hosts have used Airbnb to expand on travelling possibilities and present a more unique, personalised way of experiencing the world.
This millions of listings generate a lot of data- data that can be analyzed and used for security, business decisions, understanding of customers’ and providers’ (hosts) behaviour and performance on the platform, guiding marketing initiatives, implementation of innovation additional services.
The biggest problems Airbnb Hosts deal with? The most common problems vacation rental hosts deal with are regulations, local laws, parties, excessive turnovers, unmanageable guests, not knowing your market and finding better guests.
The theory behind the “AirBnb Effect” comes as hosts convert long-term rentals that could house local residents and families to short-term rentals for visitors, thus decreasing an already short supply of housing.
The main purpose of EDA is to help look at data before making any assumptions. It can help identify obvious errors, as well as better understand patterns within the data, detect outliers or anomalous events, find interesting relations among the variables.It can help with the detection of obvious errors, a better comprehension of data patterns, the detection of outliers or unexpected events, and the discovery of interesting correlations between variables.
Problem Statement-
Since 2008, guests and hosts have used Airbnb to expand on travelling possibilities and present a more unique, personalised way of experiencing the world.
This millions of listings generate a lot of data- data that can be analyzed and used for security, business decisions, understanding of customers’ and providers’ (hosts) behaviour and performance on the platform, guiding marketing initiatives, implementation of innovation additional services.
Define Your Business Objective?
The goal of data exploration is to learn about characteristics and potential problems of a data set without the need to formulate assumptions about the data beforehand. In statistics, data exploration is often referred to as “exploratory data analysis” and contrasts traditional hypothesis testing.
It can help with the detection of obvious errors, a better comprehension of data patterns, the detection of outliers or unexpected events, and the discovery of interesting correlations between variables.
Data Science technologies are at the core of identifying drivers of trust to engage more users and find out novel ways on how to alleviate trust. Data science technology is the key differentiator for the rapid growth of AirBnB and how it is able to make better recommendations by matching the right people together.
