# [R] Average distance in kilometers between subsets of points with ggmap /geosphere

Eric Berger er|cjberger @end|ng |rom gm@||@com
Tue Sep 24 09:50:49 CEST 2019

```You are welcome

On Tue, Sep 24, 2019 at 9:10 AM Malte Hückstädt <

> Hello Eric, thanks a lot!In fact, your tip helped me a lot. I have now
> found a solution with lappy and apply. Thank you very much!
>
> regards, malte
>
>
> Am 23.09.2019 um 09:32 schrieb Eric Berger <ericjberger using gmail.com>:
>
> Hi Malte,
> I only skimmed your question and looked at the desired output.
> I wondered if the apply function could meet your needs.
>
> m <- matrix(1:9,nrow=3)
> m <- cbind(m,apply(m,MAR=1,mean))  # MAR=1 says to apply the function
> row-wise
> m
>
> #         [,1] [,2] [,3] [,4]
> # [1,]    1    4    7    4
> # [2,]    2    5    8    5
> # [3,]    3    6    9    6
>
> HTH,
> Eric
>
>
> On Mon, Sep 23, 2019 at 10:18 AM Malte Hückstädt <
>
>> I would like to determine the geographical distances from a number of
>> addresses and determine the mean value (the mean distance) from these.
>>
>> In case the dataframe has only one row, I have found a solution:
>>
>> ```r
>> library(openxlsx)
>> #library(sf)
>> library(tidyverse)
>> library(geosphere)
>> library("ggmap")
>>
>> #API Key bestimmen
>> set_key("")
>> api_key <- ""
>>
>> #  Data
>> df <- data.frame(
>>   V1 = c("80538 München, Germany", "01328 Dresden, Germany", "80538
>> München, Germany",
>>          "07745 Jena, Germany",    "10117 Berlin, Germany"),
>>   V2 = c("82152 Planegg, Germany", "01069 Dresden, Germany", "82152
>> Planegg, Germany",
>>          "07743 Jena, Germany",    "14195 Berlin, Germany"),
>>   V3 = c("85748 Garching, Germany", "01069 Dresden, Germany",  "85748
>> Garching, Germany",
>>          NA,     "10318 Berlin, Germany"),
>>   V4 = c("80805 München, Germany", "01187 Dresden, Germany", "80805
>> München, Germany",
>>          "07745 Jena, Germany", NA), stringsAsFactors=FALSE
>> )
>>
>> #replace NA for geocode-funktion
>> df[is.na(df)] <- ""
>>
>> #slice it
>> df1 <- slice(df, 5:5)
>>
>> #  lon lat Informations
>> df_2 <- geocode(c(df1\$V1, df1\$V2,df1\$V3, df1\$V4)) %>% na.omit()
>>
>> # to Matrix
>> mat_df  <- as.matrix(df_2)
>>
>> #dist-mat
>> dist_mat <- distm(mat_df)
>>
>> #mean-dist of row 5
>> mean(dist_mat[lower.tri(dist_mat)])/1000
>> ```
>>
>> Unfortunately, I fail to implement a function that executes the code for
>> an entire data set. My current problem is, that the function does not
>> calculate the distance-averages rowwise, but calculates the average value
>> from all lines of the data set.
>>
>> ```r
>> #Funktion
>>
>> Mean_Dist <- function(df,w,x,y,z) {
>>
>>   # for (row in 1:nrow(df)) {
>>   #   dist_mat <- geocode(c(w, x, y, z))
>>   #
>>   # }
>>
>>   df <- geocode(c(w, x, y, z)) %>% na.omit() # ziehe lon lat
>>
>>   mat_df <- as.matrix(df) # schreibe diese in eine Matrix
>>
>>   dist_mat <- distm(mat_df)
>>
>>   dist_mean <- mean(dist_mat[lower.tri(dist_mat)])
>>
>>   return(dist_mean)
>> }
>>
>> df %>%  mutate(lon =  Mean_Dist(df,df\$V1, df\$V2,df\$V3, df\$V4)/1000)
>>
>> ```
>> Do you have any idea what mistake I made?
>>
>> to clarify my question: What I'm trying to create a dataframe like this
>> one (V5):
>>
>> ```r
>>   V1                     V2                     V3
>> V4                      V5
>>   <chr>                  <chr>                  <chr>
>>  <chr>                   <numeric>
>> 1 80538 München, Germany 82152 Planegg, Germany 85748 Garching, Germany
>> 80805 München, Germany Mean_Dist_row1
>> 2 01328 Dresden, Germany 01069 Dresden, Germany 01069 Dresden, Germany
>> 01187 Dresden, Germany Mean_Dist_row2
>> 3 80538 München, Germany 82152 Planegg, Germany 85748 Garching, Germany
>> 80805 München, Germany Mean_Dist_row3
>> 4 07745 Jena, Germany    07743 Jena, Germany    07745 Jena, Germany
>>  07745 Jena, Germany Mean_Dist_row4
>> 5 10117 Berlin, Germany  14195 Berlin, Germany  10318 Berlin, Germany
>>  14476 Potsdam, Germany Mean_Dist_row5
>> ```
>>
>> eg an average of the distance of each row.
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