The raw data behind the story 'Forecasting the races for governor' https://projects.fivethirtyeight.com/2018-midterm-election-forecast/governor/

`governor_national_forecast`

A dataframe with 150 rows representing national-level results of the classic, lite, and deluxe gubernatorial forecasts since Oct. 11, 2018. and 11 variables

- forecastdate
date of the forecast

- party
the party of the forecast

- model
the model of the forecast

- win_probability
the probability of the corresponding party winning

- mean_seats
the mean of the number of seats

- median_seats
the median number of seats

- p10_seats
the top 10 percentile of number of seats

- p90_seats
the top 90 percentile of number of seats

- margin
unknown

- p10_margin
the margin of p10_seats

- p90_margin
the margin of p90_seats

FiveThirtyEight’s House, Senate And Governor Models Methodology: https://fivethirtyeight.com/methodology/how-fivethirtyeights-house-and-senate-models-work/

The original dataset included a meaningless column called "state", and all variables under this column was "US". So this column was removed.