The raw data behind the story "How Every NFL Team’s Fans Lean Politically" https://fivethirtyeight.com/features/how-every-nfl-teams-fans-lean-politically: Google Trends Data.

nfl_fandom_google

Format

a data frame with 207 rows representing designated market areas and 9 variables:

dma

Designated Market Area

nfl

The percentage of search traffic in the media market region related to the NFL over the past 5 years

nba

The percentage of search traffic in the region related to the NBA over the past 5 years

mlb

The percentage of search traffic in the region related to the MLB over the past 5 years

nascar

The percentage of search traffic in the region related to NASCAR over the past 5 years

cbb

The percentage of search traffic in the region related to the CBB over the past 5 years

cfb

The percentage of search traffic in the region related to the CFB over the past 5 years

trump_2016_vote

The percentage of voters in the region who voted for Trump in the 2016 Presidential Election

Source

Google Trends https://trends.google.com/trends/.

See also

Examples

# To convert data frame to tidy data (long) format, run: library(dplyr) library(tidyr) nfl_fandom_google_tidy <- nfl_fandom_google %>% pivot_longer(-c("dma", "trump_2016_vote"), names_to = "sport", values_to = "search_traffic") %>% arrange(dma)