https://github.com/filiplangiewicz/aviationdataanalysis
✈️ Analysis of data regarding commercial flights in the USA, from October 1987 to April 2008
https://github.com/filiplangiewicz/aviationdataanalysis
analysis collaboration data-science dplyr ggplot2 shiny
Last synced: 8 months ago
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✈️ Analysis of data regarding commercial flights in the USA, from October 1987 to April 2008
- Host: GitHub
- URL: https://github.com/filiplangiewicz/aviationdataanalysis
- Owner: FilipLangiewicz
- Created: 2023-04-29T16:10:57.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-02-17T15:10:49.000Z (over 2 years ago)
- Last Synced: 2025-03-15T13:11:18.520Z (about 1 year ago)
- Topics: analysis, collaboration, data-science, dplyr, ggplot2, shiny
- Language: R
- Homepage:
- Size: 35 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Aviation data analysis
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We analyzed data on airline time efficiency that were prepared and made public as part of the American Statistical Association Data Expo 2009: Airline on-time performance competition. Currently, these data are available in the Harvard Dataverse Repository (see [2008, “Data Expo 2009: Airline on time data”, [https://doi.org/10.7910/DVN/HG7NV7](https://doi.org/10.7910/DVN/HG7NV7), Harvard Dataverse, V1]).
We asked ourselves the following questions and tried to find answers in the available data:
1. Of the ten largest airports in the United States, which airport has the lowest departure delays and lowest cancellation rates? (🥇 Houston - George Bush)
2. How has the carrier market and arrival delays changed for the largest airline companies in the United States?
3. What impact did employee strikes have on the condition and quality of services of individual airline companies?
4. How does this translate into average delay compared to other companies and the overall average?
The summary presentation can be found [here](https://github.com/FilipLangiewicz/Projekt_PDU_02/blob/main/Analiza.pptx).
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