https://github.com/vbhvsingh0/nflteam_corr_population

The goal of this project is to find the correlation in between NFL teams' win and loss with the population of the city.
https://github.com/vbhvsingh0/nflteam_corr_population

data-analysis data-cleaning-and-preprocessing data-manipulation-with-pandas numpy-library pandas-python pearson-correlation python3

Last synced: 16 days ago
JSON representation

The goal of this project is to find the correlation in between NFL teams' win and loss with the population of the city.

• Host: GitHub
• URL: https://github.com/vbhvsingh0/nflteam_corr_population
• Owner: vbhvsingh0
• Created: 2024-07-09T22:05:59.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-07-09T23:10:32.000Z (7 months ago)
• Last Synced: 2024-11-14T16:46:24.501Z (3 months ago)
• Topics: data-analysis, data-cleaning-and-preprocessing, data-manipulation-with-pandas, numpy-library, pandas-python, pearson-correlation, python3
• Language: HTML
• Homepage:
• Size: 81.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# NFLteam_corr_population

The goal of this project is to find the correlation between the USA Sports teams' wins with respect to the population of the city. 

Note: This project was a part of the Coursera course, "Introduction to Data Science in Python" offered by University of Michigan.

A file of metropolitan regions and associated sports teams was taken from assets/wikipedia_data.html . Each of these regions may have one or more teams from the "Big 4": NFL (football) , MLB (Baseball), NBA (basketball) or NHL (Hockey). For each sport I would like to answer the question: what is the win/loss ratio's correlation with the population of the city it is in? Win/Loss ratio refers to the number of wins over the number of wins plus the number of losses. The data for the win-loss ratio for the four sports are provided as .csv files. To calculate the correlation with pearsonr, two ordered lists of values were involved, the populations from the wikipedia_data.html file and the win/loss ratio for a given sport in the same order. The win/loss ratios for those cities which have multiple teams of a single sport were averaged. 

Note: The analysis was done only for the data after the year 2018.

Correlations were calculated separately for each of the 4 sports. The scripts written to calculate correlations are in the files nhl_corr.py, nba_corr.py, mlb_corr.py, nfl_corr.py for NHL, NBA, MLB, and NFL respectively.

Observation: Interestingly, the NBA, NFL, and MLB showed a positive correlation, but the NHL had a negative correlation.