Please help
I need to calculate the distance of 3 or more points that are stacked on each other. the reason for this is so that I can see the route that was taken by this person based on the data from the tracking app.
And the distance is stacked into of each other. And I need to calculate this for different users.
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Hello,
I'm sure you shared this image with the best intentions, but perhaps you didnt realise what it implies.
If someone wished to use example data to test code against, they would type it out from your screenshot...
This is very unlikely to happen, and so it reduces the likelihood you will receive the help you desire.
Therefore please see this guide on how to reprex data. Key to this is use of either datapasta, or dput() to share your data as code
Thank you for letting me know, I'll send the coordinates:
latitude:
c(5.6120837, 5.6120837, 5.6120837, 5.6120837, 5.6120837, 5.6120837,
5.6120837, 5.6120837, 5.6120837, 5.6120837, 5.6122173, 5.6120837,
5.6120683, 5.6120837, 5.6120842, 5.6120842, 5.6120837, 5.6120837,
5.6120509, 5.6120508, 5.6120518, 5.6120518, 5.6120518, 5.6120518,
5.6120518, 5.6120518, 5.6120518, 5.6120518, 5.6120518, 5.6120711,
5.6120553, 5.6120314, 5.61203, 5.6120792, 5.6120837, 5.6120837,
5.6120837, 5.6120608, 5.6120837, 5.6120837)
longitude:
c(-0.0733074, -0.0733074, -0.0733074, -0.0733074, -0.0733074,
-0.0733074, -0.0733074, -0.0733074, -0.0733074, -0.0733074, -0.073484,
-0.0733074, -0.073312, -0.0733074, -0.0733759, -0.0733759, -0.0733074,
-0.0733074, -0.0733277, -0.0733266, -0.0733282, -0.0733282, -0.0733282,
-0.0733282, -0.0733282, -0.0733282, -0.0733282, -0.0733282, -0.0733282,
-0.0733075, -0.0733259, -0.0733516, -0.0733534, -0.0733438, -0.0733074,
-0.0733074, -0.0733074, -0.0732539, -0.0733074, -0.0733074)
Im make the image like data frame using ORC. For calculate the distances you need this columns?
data-> structure(list(coordinate = c("[-0.0733074,5.6120837)", "[-0.0733074,5.6120837]",
"[-0.0733074,5.6120837]", "[-0.0733074,5.6120837)", "[-0.0733074,5.6120837]",
"[-0.0733074,5.6120837]", "[-0.0733074,5.6120837]", "[-0.0733074,5.6120837]",
"[-0.0733074,5.6120837])", "[-0.0733074,5.6120837]", "[-0.073484,5.6122173}",
"[-0.0733074,5.6120837]", "[-0.073312,5.6120683)", "[-0.0733074,5.6120837]",
"[-0.0733759,5.6120842)", "[-0.0733759,5.6120842)", "[-0.0733074,5.6120837]",
"[-0.0733074,5.6120837]", "[-0.0733277,5.6120509}", "[-0.0733266,5.6120508)",
"[-0.0733282,5.6120518]", "[-0.0733282,5.6120518)", "[-0.0733282,5.6120518)",
"[-0.0733282,5.6120518})", "[-0.0733282,5.6120518})", "[-0.0733282,5.6120518]",
"[-0.0733282,5.6120518})", "[-0.0733282,5.6120518]", "[-0.0733282,5.6120518})",
"[-0.0733075,5.6120711)", "[-0.0733259,5.6120553}", "[-0.0733516,5.6120314)",
"[-0.0733534,5.61203)", "[-0.0733438,5.6120792)", "[-0.0733074,5.6120837]",
"[-0.0733074,5.6120837]", "[-0.0733074,5.6120837]", "[-0.0732539,5.6120608)",
"[-0.0733074,5.6120837}"), lalitude = c("5.612084", "5.612084",
"5.612084", "5.612084", "5.612084", "5.612084", "5.612084", "5.612084",
"5.612084", "5.612084", "5.612217", "5.612084", "5.612068", "5.612084",
"5.612084", "5.612084", "5.612084", "5.612084", "5.612051", "5.612051",
"5.612052", "§.612052", "5.612052", "§.612052", "5.612052",
"5.612052", "§.612052", "5.612052", "§.612052", "5.612071",
"§.612055", "5.612031", "5.612030", "5.612079", "5.612084",
"5.612084", "5.612084", "5.612061", "5.612084"), longitude = c("-0.0733074",
"-0.0733074", "-0.0733074", "-0.0733074", "-0.0733074", "-0.0733074",
"-0.0733074", "-0.0733074", "-0.0733074", "-0.0733074", "-0.0734840",
"-0.0733074", "-0.0733120", "-0.0733074", "-0.0733759", "-0.0733759",
"-0.0733074", "-0.0733074", "-0.0733277", "-0.0733266", "-~0.0733282",
"-0.0733282", "-0.0733282", "-0.0733282", "-0.0733282", "-0.0733282",
"-0.0733282", "-0.0733282", "-0.0733282", "-0.0733075", "-0.0733259",
"-0.0733516", "-0.0733534", "-0.0733438", "-0.0733074", "-0.0733074",
"-0.0733074", "-0.0732539", "-0.0733074")), class = "data.frame", row.names = c(NA,
-39L))
# coordinate lalitude longitude
# 1 [-0.0733074,5.6120837) 5.612084 -0.0733074
# 2 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 3 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 4 [-0.0733074,5.6120837) 5.612084 -0.0733074
# 5 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 6 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 7 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 8 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 9 [-0.0733074,5.6120837]) 5.612084 -0.0733074
# 10 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 11 [-0.073484,5.6122173} 5.612217 -0.0734840
# 12 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 13 [-0.073312,5.6120683) 5.612068 -0.0733120
# 14 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 15 [-0.0733759,5.6120842) 5.612084 -0.0733759
# 16 [-0.0733759,5.6120842) 5.612084 -0.0733759
# 17 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 18 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 19 [-0.0733277,5.6120509} 5.612051 -0.0733277
# 20 [-0.0733266,5.6120508) 5.612051 -0.0733266
# 21 [-0.0733282,5.6120518] 5.612052 -~0.0733282
# 22 [-0.0733282,5.6120518) §.612052 -0.0733282
# 23 [-0.0733282,5.6120518) 5.612052 -0.0733282
# 24 [-0.0733282,5.6120518}) §.612052 -0.0733282
# 25 [-0.0733282,5.6120518}) 5.612052 -0.0733282
# 26 [-0.0733282,5.6120518] 5.612052 -0.0733282
# 27 [-0.0733282,5.6120518}) §.612052 -0.0733282
# 28 [-0.0733282,5.6120518] 5.612052 -0.0733282
# 29 [-0.0733282,5.6120518}) §.612052 -0.0733282
# 30 [-0.0733075,5.6120711) 5.612071 -0.0733075
# 31 [-0.0733259,5.6120553} §.612055 -0.0733259
# 32 [-0.0733516,5.6120314) 5.612031 -0.0733516
# 33 [-0.0733534,5.61203) 5.612030 -0.0733534
# 34 [-0.0733438,5.6120792) 5.612079 -0.0733438
# 35 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 36 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 37 [-0.0733074,5.6120837] 5.612084 -0.0733074
# 38 [-0.0732539,5.6120608) 5.612061 -0.0732539
# 39 [-0.0733074,5.6120837} 5.612084 -0.0733074
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