Baselight
Sign In

Cyclistic Trips 2021-12 T0–2022-12

divvy trip data from 2021 December to 2022 December

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212

Loading...
Loading...

About this Dataset

Cyclistic Trips 2021-12 T0–2022-12

In 2016, Cyclistic launched a successful bike-share offering. Since then, the program has grown to a fleet of 5,824 bicycles that are geotracked and locked into a network of 692 stations across Chicago. The bikes can be unlocked from one station and returned to any other station in the system anytime.
Until now, Cyclistic’s marketing strategy relied on building general awareness and appealing to broad consumer segments. One approach that helped make these things possible was the flexibility of its pricing plans: single-ride passes, full-day passes, and annual memberships. Customers who purchase single-ride or full-day passes are referred to as casual riders. Customers who purchase annual memberships are Cyclistic members.
Cyclistic’s finance analysts have concluded that annual members are much more profitable than casual riders. Although the pricing flexibility helps Cyclistic attract more customers, Moreno believes that maximizing the number of annual members will be key to future growth. Rather than creating a marketing campaign that targets all-new customers, Moreno believes there is a very good chance to convert casual riders into members. She notes that casual riders are already aware of the Cyclistic program and have chosen Cyclistic for their mobility needs.

Tables

N 202112 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202112_divvy_tripdata
  • 12.62 MB
  • 247540 rows
  • 13 columns
Loading... 

CREATE TABLE n_202112_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202201 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202201_divvy_tripdata
  • 5.28 MB
  • 103770 rows
  • 13 columns
Loading... 

CREATE TABLE n_202201_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202202 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202202_divvy_tripdata
  • 5.83 MB
  • 115609 rows
  • 13 columns
Loading... 

CREATE TABLE n_202202_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202203 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202203_divvy_tripdata
  • 13.58 MB
  • 284042 rows
  • 13 columns
Loading... 

CREATE TABLE n_202203_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202204 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202204_divvy_tripdata
  • 17.81 MB
  • 371249 rows
  • 13 columns
Loading... 

CREATE TABLE n_202204_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202205 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202205_divvy_tripdata
  • 29.88 MB
  • 634858 rows
  • 13 columns
Loading... 

CREATE TABLE n_202205_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202206 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202206_divvy_tripdata
  • 35.78 MB
  • 769204 rows
  • 13 columns
Loading... 

CREATE TABLE n_202206_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202207 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202207_divvy_tripdata
  • 39.4 MB
  • 823488 rows
  • 13 columns
Loading... 

CREATE TABLE n_202207_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202208 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202208_divvy_tripdata
  • 37.96 MB
  • 785932 rows
  • 13 columns
Loading... 

CREATE TABLE n_202208_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202209 Divvy Publictripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202209_divvy_publictripdata
  • 33.78 MB
  • 701339 rows
  • 13 columns
Loading... 

CREATE TABLE n_202209_divvy_publictripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202210 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202210_divvy_tripdata
  • 27.04 MB
  • 558685 rows
  • 13 columns
Loading... 

CREATE TABLE n_202210_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

N 202211 Divvy Tripdata

@kaggle.pyaephyoaung_cyclistic_trips_202112_t0_202212.n_202211_divvy_tripdata
  • 16.68 MB
  • 337735 rows
  • 13 columns
Loading... 

CREATE TABLE n_202211_divvy_tripdata (
  "ride_id" VARCHAR,
  "rideable_type" VARCHAR,
  "started_at" TIMESTAMP,
  "ended_at" TIMESTAMP,
  "start_station_name" VARCHAR,
  "start_station_id" VARCHAR,
  "end_station_name" VARCHAR,
  "end_station_id" VARCHAR,
  "start_lat" DOUBLE,
  "start_lng" DOUBLE,
  "end_lat" DOUBLE,
  "end_lng" DOUBLE,
  "member_casual" VARCHAR
);

Share link

Anyone who has the link will be able to view this.