data_buoy_gaps: NOAA buoy weather data
In forecastML: Time Series Forecasting with Machine Learning Methods
Description
Usage
Format
Source
Description
A dataset containing daily average sensor measurements of several environmental
conditions collected by 14 buoys in Lake Michigan from 2012 through 2018. This
dataset is identical to the data_buoy dataset except that there are gaps in
the daily sensor data. Running fill_gaps() on data_buoy_gaps will
produce data_buoy.
Usage
1
Format
A data.frame with 23,646 rows and 9 columns:
- date
date
- wind_spd
average daily wind speed in kts
- buoy_id
the station ID for each buoy
- lat
latitude
- lon
longitude
- day
day of year
- year
calendar year
- air_temperature
air temperature in degrees Fahrenheit
- sea_surface_temperature
water temperature in degrees Fahrenheit
Source
forecastML documentation built on July 8, 2020, 7:27 p.m.
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Description Usage Format Source
Description
A dataset containing daily average sensor measurements of several environmental
conditions collected by 14 buoys in Lake Michigan from 2012 through 2018. This
dataset is identical to the data_buoy dataset except that there are gaps in
the daily sensor data. Running fill_gaps() on data_buoy_gaps will
produce data_buoy.
Usage
1 |
Format
A data.frame with 23,646 rows and 9 columns:
- date
date
- wind_spd
average daily wind speed in kts
- buoy_id
the station ID for each buoy
- lat
latitude
- lon
longitude
- day
day of year
- year
calendar year
- air_temperature
air temperature in degrees Fahrenheit
- sea_surface_temperature
water temperature in degrees Fahrenheit
Source
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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