https://github.com/winniecirino/chicago-trips-by-distance-analysis

This repository focus on the analysis of the Chicago dataset. The focus of the analysis is to understand trip patterns, identify key metrics, and provide actionable insights for business and urban planning decisions.
https://github.com/winniecirino/chicago-trips-by-distance-analysis

sql sql-server sqlserver

Last synced: about 1 month ago
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This repository focus on the analysis of the Chicago dataset. The focus of the analysis is to understand trip patterns, identify key metrics, and provide actionable insights for business and urban planning decisions.

• Host: GitHub
• URL: https://github.com/winniecirino/chicago-trips-by-distance-analysis
• Owner: WinnieCIRINO
• Created: 2024-08-08T20:19:44.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-08-16T06:29:02.000Z (6 months ago)
• Last Synced: 2024-11-05T10:39:01.743Z (3 months ago)
• Topics: sql, sql-server, sqlserver
• Homepage:
• Size: 14.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Chicago-Trips-by-Distance-Analysis

This repository focus on the analysis of the Chicago dataset. The focus of the analysis is to understand trip patterns, identify key matrics, and provide actionable insights for business and urban planning decisions. 

## Dataset

The dataset includes information on trips taken within Chicago, detailing the distance of each trip and various associated metrics.

## Analysis

The analysis includes the following aspects:

**Total Trips by Month**: Analysis of total number of trips recorded each month.

**Population Staying Home vs Not Staying Home**: Examination of the population trends staying home or being out.

**Total Trips in Miles**: Aggregation of the total distance travelled in all trips. 

**Population trends by Season, Month and Year**: Breakdown of population staying home or not by different time periods (seasonal, monthly, yearly)

## Key Metrics

- **Total Trips**: Number of trips recorded per month.

- **Total Distance Traveled**: Sum of trip distances.

- **Population Statistics**: Insights into the behavior of the population in terms of staying home or being out, segmented by various time periods.

## Requirements

- **Excel**: Used for cleaning and initial data exploration.

- **SQL**: Employed for querying and data wrangling.

- **Power BI**: Utilized for creating visualizations and presenting findings.

## Analysis and Visualization (Power BI Report)

[![Trips](https://github.com/user-attachments/assets/a7a303c6-338d-436b-9314-caca936dfe5f)](https://www.novypro.com/profile_projects/winnie-cirino?Popup=memberProject&Data=1704872007823x826201699671272200)

## Access the Dataset

The dataset used for this analysis can be accessed [here](https://drive.google.com/drive/folders/1_-CNVcs-eDxPrOYq_fdkg58Hr3Y-BVv1?usp=drive_link).