The latitude and longitude of other cities are stored in ‘’latitudes’ and ‘longitudes’ respectively. We type the following command with the first two arguments being the latitude (40.697132) and longitude (-73.931351), respectively, of New York. Let’s say we wish to find the distance of New York from other cities in the US. Calculating the Distance of New York From Other Cities The double format is more precise and accurate than float. Whenever working with distances, or the geodist command, it is a good idea to store values in variables with the double format rather than the float format. Other optional options can also be added.īy default, this command generates distances in kilometers. The option of generate()is necessary, and allows us to specify the name of the variable that will be generated to store the distance between the two locations. The latitude must always be written before the longitude. The first two arguments are the latitude and longitude of the first location, followed by the latitude and longitude of the second location. The general syntax of the command is as follows: geodist lat1 lon1 lat2 lon2, generate(new_dist_var) Stata’s working directory can be changed through: cd “directory path” Syntax of geodist
Make sure the working directory of your Stata file is the same as the working directory of the data file. tidy ( near_station, number = 1 ) #> # A tibble: 1 × 7 #> latitude longitude ref_latitude ref_longitude is_lat_lon name id #> #> 1 latitude longitude 38.9 - 77.To load the dataset, we type: use "distance.dta", clear #> 15 National Museum of African American Histor… 38.9 - 77.0 2611. #> 14 National Museum of American History 38.9 - 77.0 2393. #> 8 National Museum of Natural History 38.9 - 77.0 2073. #> 7 Hirshhorn Museum and Sculpture Garden 38.9 - 77.0 2008. #> 4 Smithsonian American Art Museum 38.9 - 77.0 1636. #> 3 National Museum of the American Indian 38.9 - 77.0 1571. idĪ character string that is unique to this step to identify it.ĭata ( Smithsonian, package = "modeldata" ) # How close are the museums to Union Station? near_station % update_role ( name, new_role = "location" ) %>% step_geodist ( lat = latitude, lon = longitude, log = FALSE, ref_lat = 38.8986312, ref_lon = - 77.0062457, is_lat_lon = TRUE ) %>% prep (training = Smithsonian ) bake ( near_station, new_data = NULL ) %>% arrange ( geo_dist ) #> # A tibble: 20 × 4 #> name latitude longitude geo_dist #> #> 1 National Postal Museum 38.9 - 77.0 367. The computations for subsequent operations. processing the outcome variable(s)).Ĭare should be taken when using skip = TRUE as it may affect When prep() is run, some operations may not be able to beĬonducted on new data (e.g. Recipe is baked by bake()? While all operations are baked If a column exists with this name, an error isĪ character string of variable names that willīe populated (eventually) by the terms argument.
.jpg "geodist in r")
logĪ logical: should the distance be transformed byĪ single character value to use for the new Default is TRUE and for recipesĬreated from previous versions of recipes, a value of FALSE is used. TRUE the Haversine formula is used and the returned result is meters. ref_lon, ref_latĪ logical: Are coordinates in latitude and longitude? If trainedĪ logical to indicate if the quantities for The original variables will be used as predictors in a model. They be assigned? By default, the new columns created by this step from roleįor model terms created by this step, what analysis role should Selector functions to choose which variables are
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