![]() ![]() ![]() The closest I found is here: but it fails because it can't find a function called ' list_extract'. use clear collapse (mean) avgageage, by (famid) list famid avgage 1. If you have any remaining questions, issues, or concerns about the data. In this article, we introduce the community-contributed command georoute, which retrieves travel distance and travel time. The following collapse command does the exact same thing as above, except that the average of age is named avgage and we have explicitly told the collapse command that we want it to compute the mean. For any pair of countries, from 1948 to 2020, Gravity provides all the information required to estimate gravity equations: trade flows, geographical distances, trade facilitation measures, macroeconomic indicators, etc. I'm struggling to find a function that does this. Recently, several commands have been implemented for this purpose ( traveltime, traveltime3, mqtime, osrmtime ), but most of them became obsolete only a few months after their introduction or appear complicated to use. The second thing that might help is restarting your Stata. I haven't checked the Google API in a while but it might just return the centroids for these types of cases. > -Original Message- > From: mailto: On Behalf Of Robert Picard > Sent: 15:12 > To: > Subject: Re: st. ![]() So, you would need a street address along with the city/state to get reasonable results. Just one (I hope) more question: I'm using Stata 10, and am not sure what the equivalent of 'merge 1:1 n' is. This article explains how to use geodist command in stata to calcuate. I would like to calculate the distance between each of the 2 points in miles and add it as a new column. The first is that geocoding is used for point locations, not polygons. The calculator uses Haversine formula to calculate the distance between the two. GEODIST: Stata module to compute geographical distances. I have a data frame with 6 columns: - location id 1 Calculate Great Circle distances using latitude and longitude. ![]()
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