Name: Cornell Car Rental Dataset
Creator: Kaggle
License: https://creativecommons.org/licenses/by/4.0/

About this Dataset

Cornell Car Rental Dataset

Context

As a Product Manager for a startup I needed to make certain data driven decisions which involved the car rental industry. So I scraped the web and built this dataset myself. I thought to make is public as a way to give back to the community.

Here is a Medium Post by me describing some insights from this dataset and releasing the dataset to public:
https://link.medium.com/Yduf7ceYC8

Content

The content is acquired during the time of July 2020 for major US cities.

Acknowledgements

The scraping scripts I used were built off of certain StackOverflow responses.

Inspiration

Some of the answers this dataset can help unwind is:

Which car makes and models are popular and in which cities
What is the typical fare of car rental in various major cities
Is there a Market gap or are some markets oversaturated
Users can also explore if the ratings on the sites have any co-relation or do they appear suspicious as most are close to 5 ratings.

Tables

Carrentaldata

@kaggle.kushleshkumar_cornell_car_rental_dataset.carrentaldata

216.94 kB
5,851 rows
15 columns

CREATE TABLE carrentaldata (
  "fueltype" VARCHAR,
  "rating" DOUBLE,
  "rentertripstaken" BIGINT,
  "reviewcount" BIGINT,
  "location_city" VARCHAR,
  "location_country" VARCHAR,
  "location_latitude" DOUBLE,
  "location_longitude" DOUBLE,
  "location_state" VARCHAR,
  "owner_id" BIGINT,
  "rate_daily" BIGINT,
  "vehicle_make" VARCHAR,
  "vehicle_model" VARCHAR,
  "vehicle_type" VARCHAR,
  "vehicle_year" BIGINT
);

Carrentaldatav1

@kaggle.kushleshkumar_cornell_car_rental_dataset.carrentaldatav1

220.88 kB
5,851 rows
16 columns

CREATE TABLE carrentaldatav1 (
  "fueltype" VARCHAR,
  "rating" DOUBLE,
  "rentertripstaken" DOUBLE,
  "reviewcount" DOUBLE,
  "location_city" VARCHAR,
  "location_country" VARCHAR,
  "location_latitude" DOUBLE,
  "location_longitude" DOUBLE,
  "location_state" VARCHAR,
  "owner_id" DOUBLE,
  "rate_daily" DOUBLE,
  "vehicle_make" VARCHAR,
  "vehicle_model" VARCHAR,
  "vehicle_type" VARCHAR,
  "vehicle_year" DOUBLE,
  "airportcity" VARCHAR
);