Topic: divvy-bikes Goto Github
Some thing interesting about divvy-bikes
Some thing interesting about divvy-bikes
divvy-bikes,This case study is about a fictitious company, Cyclistic. Where I will answer business questions, following the steps of the data analysis process: Ask, Prepare, Process, Analyze, Share and Act.
User: baguilar6174
Home Page: https://www.kaggle.com/code/bryana/cyclistic-bike-share-analysis
divvy-bikes,A Python utility to scrape and export your Divvy bike data to .csv
User: colemanmitch
divvy-bikes,An end-to-end data pipeline which extracts divvy bikeshare data from web loads it into data lake and datawarehouse transforms it using dbt and finally , a dashboard to visualize the data using looker studio, the pipeline is orchestrated using prefect
User: fozan-talat
divvy-bikes,A comprehensive analysis and insights derived from the Google Data Analytics Capstone Project focused on Cyclistic, a bike-share program.
User: mukaddasa
divvy-bikes,Portfolio
User: nadiia-analyst
divvy-bikes,Scripts to combine various Chicago transit data feeds
User: nkasimer
divvy-bikes,Regression and Decision Tree Analysis of Divvy bike dataset to estimate bike demand based on weather conditions
User: pranavshivk97
divvy-bikes,A case study on the fictional bike-share company Cyclistic's trip data, based on Chicago Divvy public dataset.
User: renegamino012
divvy-bikes,Several classifier models to predict non-member vs member rider status based off of ride data for Divvy Bikes users. Trained off of 13 months of past ride data.
User: ruiawang
divvy-bikes,Analysis of Chicago's rideshare biking service, Divvy, in Q3 of 2019.
User: ruthhinkle
divvy-bikes,Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago.
User: ruthhinkle
divvy-bikes,Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago via Flask application. Must be run locally to use.
User: ruthhinkle
divvy-bikes,Developed a relational database that will enable quick response and analysis on the current state of Divvy’s operations in regard to ridership, station locations, other factors affecting them. Then built a scoring model to optimize the number of stations and bikes allocated by zip codes
User: tam-ng
divvy-bikes,This project is to use Tableau to visualize the usage patterns of Divvy bikes in Chicago. By analyzing the trip data provided, we can gain insights into when, where, and how bikes are being used. This information can be useful for Divvy and the City of Chicago in planning future bike infrastructure and promoting sustainable transportation options.
User: visheshgupta-ba
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