An R interface to the
PredictIt API (original) (raw)
The rpredictit package provides an interface to the PredictIt public API (https://www.predictit.org/api/marketdata/all/). In addition to providing a wrapper to retrieve market data, this package includes visualization and analysis functions.
rpredictit is not affiliated with any predictive markets and is presented for informational purposes only. Always confirm with your own research before making an investment. License to use data made available via the API is for non-commercial use and PredictIt is the sole source of such data.
Installation
You may install the stable version from CRAN, or the development version using devtools:
# install from CRAN
install.packages('rpredictit')
# or the development version, via devtools
devtools::install_github('danielkovtun/rpredictit')Usage
Demo Shiny Application
To start off, try running a demo Shiny application included with the package by running:
library(rpredictit)
runExample('demo')All Markets
Try rpredictit::all_markets() to return a tibble containing bid and ask data for all PredictIt markets:
library(rpredictit)
all_markets()
# A tibble: 1,096 x 20
id name shortName image url timeStamp status contract_id dateEnd contract_image contract_name contract_shortN… contract_status lastTradePrice bestBuyYesCost
<int> <chr> <chr> <chr> <chr> <dttm> <chr> <int> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
1 2721 Whic… Which pa… http… http… 2019-12-23 14:53:45 Open 4390 N/A https://az620… Democratic Democratic Open 0.52 0.53
2 2721 Whic… Which pa… http… http… 2019-12-23 14:53:45 Open 4389 N/A https://az620… Republican Republican Open 0.49 0.49
3 2721 Whic… Which pa… http… http… 2019-12-23 14:53:45 Open 4388 N/A https://az620… Libertarian Libertarian Open 0.02 0.03
4 2721 Whic… Which pa… http… http… 2019-12-23 14:53:45 Open 4391 N/A https://az620… Green Green Open 0.02 0.03
5 2747 Will… Will Cub… http… http… 2019-12-23 14:53:45 Open 4495 2020-1… https://az620… Will Mark Cu… Will Cuban run … Open 0.05 0.07
6 2875 Will… Will Cuo… http… http… 2019-12-23 14:53:45 Open 5121 2020-1… https://az620… Will Andrew … Will Cuomo run … Open 0.06 0.09
7 2901 Will… Woman pr… http… http… 2019-12-23 14:53:45 Open 5215 N/A https://az620… Will a woman… Woman president… Open 0.12 0.12
8 2902 Will… Will the… http… http… 2019-12-23 14:53:45 Open 5216 N/A https://az620… Will the 202… Will the 2020 D… Open 0.22 0.23
9 2903 Will… Will the… http… http… 2019-12-23 14:53:45 Open 5217 N/A https://az620… Will the 202… Will the 2020 G… Open 0.04 0.05
10 2992 Will… Will Zuc… http… http… 2019-12-23 14:53:45 Open 5534 2020-1… https://az620… Will Faceboo… Will Zuckerberg… Open 0.03 0.04
# … with 1,086 more rows, and 5 more variables: bestBuyNoCost <dbl>, bestSellYesCost <dbl>, bestSellNoCost <dbl>, lastClosePrice <dbl>, displayOrder <int>Interactive Table
Alternatively, to return an interactive htmlwidget (DT::datatable) table containing HTML formatted market data, pass the returned bid/ask data to rpredictit::markets_table():
data <- rpredictit::all_markets()
rpredictit::markets_table(data)Interactive Plot
To plot historical prices, download a ‘csv’ file for a specific contract from PredictIt’s website and pass the file path torpredictit::parse_historical_csv(). Then, pass in the returned contract data object torpredictit::historical_plot():
filename <- "What_will_be_the_balance_of_power_in_Congress_after_the_2020_election.csv"
csv_path <- system.file("extdata", filename, package = "rpredictit")
contract_data <- rpredictit::parse_historical_csv(csv_path)
rpredictit::historical_plot(contract_data)Individual Market
To return data for a specific market, userpredictit::single_market(id), where id refers to the numerical code pertaining to the market of interest. You can find a market’s numerical code by consulting its URL or by first calling the all markets API (all_markets())
markets <- rpredictit::all_markets()
id <- markets$id[1]
rpredictit::single_market(id)
# A tibble: 4 x 20
id name shortName image url timeStamp status contract_id dateEnd contract_image contract_name contract_shortN… contract_status lastTradePrice bestBuyYesCost
<int> <chr> <chr> <chr> <chr> <dttm> <chr> <int> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
1 2721 Whic… Which pa… http… http… 2019-12-23 14:51:03 Open 4390 N/A https://az620… Democratic Democratic Open 0.52 0.53
2 2721 Whic… Which pa… http… http… 2019-12-23 14:51:03 Open 4389 N/A https://az620… Republican Republican Open 0.49 0.49
3 2721 Whic… Which pa… http… http… 2019-12-23 14:51:03 Open 4388 N/A https://az620… Libertarian Libertarian Open 0.02 0.03
4 2721 Whic… Which pa… http… http… 2019-12-23 14:51:03 Open 4391 N/A https://az620… Green Green Open 0.02 0.03
# … with 5 more variables: bestBuyNoCost <dbl>, bestSellYesCost <dbl>, bestSellNoCost <dbl>, lastClosePrice <dbl>, displayOrder <int>See the full documentation at https://danielkovtun.github.io/rpredictit/.