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How would I be able to add in two columns to this dataset, 1 with the teams conference (NFC or
AFC) and one with the specific location to mark their division (North, South, East, West)
For example: For the first row here, before Panthers, I want one column that says NFC to
represent the conference, and one that says South to represent the division, since Panthers are in
the NFC South. Pretty much just need to understand how to add columns to a dataset. Can
someone please help. This is in R. Thank you
I started by combining team (city) and team name together because there was no reason to have
two seperate columns. Then I narrowed down the data to only showing 2015 to 2019 because I
got into football around 2015 and I want to see which teams were the best and worst during that
time period. Then I put the teams in order of decreasing wins, so the teams with the most wins
were shown at the top for each year. Lastly, for this project, I wanted to focus on margin of
victory, strength of schedule, simple rating, and offensive and defensive rankings, so I left out
the points for, against, and differential, becausee margin of victory calculates those statstics into
it. NFLStandings <- NFLStandings % > % unite(team, team name, sep = iI") % > % filter ( year
> 2014 ) % > % arrange(year, desc(wins)) % % select(team, year, wins, loss, margin_of_victory,
strength_of_schedule, simple_rating, offensive_ranking, defensive_ranking, playoffs, sb_winner)
NFLStandings % > % head

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How would I be able to add in two columns to this dataset- 1 with the (1).pdf

  • 1. How would I be able to add in two columns to this dataset, 1 with the teams conference (NFC or AFC) and one with the specific location to mark their division (North, South, East, West) For example: For the first row here, before Panthers, I want one column that says NFC to represent the conference, and one that says South to represent the division, since Panthers are in the NFC South. Pretty much just need to understand how to add columns to a dataset. Can someone please help. This is in R. Thank you I started by combining team (city) and team name together because there was no reason to have two seperate columns. Then I narrowed down the data to only showing 2015 to 2019 because I got into football around 2015 and I want to see which teams were the best and worst during that time period. Then I put the teams in order of decreasing wins, so the teams with the most wins were shown at the top for each year. Lastly, for this project, I wanted to focus on margin of victory, strength of schedule, simple rating, and offensive and defensive rankings, so I left out the points for, against, and differential, becausee margin of victory calculates those statstics into it. NFLStandings <- NFLStandings % > % unite(team, team name, sep = iI") % > % filter ( year > 2014 ) % > % arrange(year, desc(wins)) % % select(team, year, wins, loss, margin_of_victory, strength_of_schedule, simple_rating, offensive_ranking, defensive_ranking, playoffs, sb_winner) NFLStandings % > % head