数据框架的结构
> str(df)
'data.frame': 459 obs. of 6 variables:
$ Source : chr "Mumbai" "Mumbai" "Bangalore" "Bangalore" ...
$ Destination: chr "Bangalore" "Bangalore" "Chennai" "Cochin" ...
$ src_loc :'data.frame': 459 obs. of 2 variables:
..$ lon: num 72.9 72.9 77.6 77.6 73.9 ...
..$ lat: num 19.1 19.1 13 13 18.5 ...
$ dest_loc :'data.frame': 459 obs. of 2 variables:
..$ lon: num 77.6 77.6 80.3 76.3 78.5 ...
..$ lat: num 12.97 12.97 13.08 9.93 17.39 ...
$ route_line:List of 459
..$ :'data.frame': 219 obs. of 2 variables:
.. ..$ lat: num 19.1 19.1 19.1 19.1 19.1 ...
.. ..$ lon: num 72.9 72.9 72.9 72.9 73 ...
..$ :'data.frame': 219 obs. of 2 variables:
.. ..$ lat: num 19.1 19.1 19.1 19.1 19.1 ...
.. ..$ lon: num 72.9 72.9 72.9 72.9 73 ...
..$ :'data.frame': 244 obs. of 2 variables:
.. ..$ lat: num 13 13 13 13 13 ...
.. ..$ lon: num 77.6 77.6 77.6 77.6 77.6 ...
..$ :'data.frame': 228 obs. of 2 variables:
.. ..$ lat: num 13 13 13 12.9 12.9 ...
.. ..$ lon: num 77.6 77.6 77.6 77.6 77.6 ...
..$ :'data.frame': 232 obs. of 2 variables:
.. ..$ lat: num 18.5 18.5 18.5 18.5 18.5 ...
.. ..$ lon: num 73.9 73.9 73.9 73.9 73.9 ...
..$ :'data.frame': 234 obs. of 2 variables:
.. ..$ lat: num 15.4 15.4 15.4 15.4 15.4 ...
.. ..$ lon: num 75.1 75.1 75.1 75.1 75.1 ...
..$ :'data.frame': 218 obs. of 2 variables:
.. ..$ lat: num 17.4 17.4 17.4 17.5 17.5 ...
.. ..$ lon: num 78.5 78.5 78.5 78.5 78.5 ...
so o。
> df$route_line[[1]] #gives a data frame
lat lon
1 19.07597 72.87765
2 19.06575 72.89918
3 19.06331 72.91443
4 19.05159 72.93661
5 19.06758 72.98437
6 19.06653 73.02000
7 19.04099 73.02868
8 19.02309 73.04452
9 19.03844 73.07676
10 18.99688 73.13215
11 18.98191 73.14718
12 18.96049 73.15789
13 18.94201 73.15694
14 18.92484 73.16662
15 18.89439 73.20433
16 18.84075 73.24026
17 18.81434 73.27669
18 18.79409 73.29148
19 18.77373 73.32182
20 18.77023 73.33760
21 18.76414 73.34698
22 18.77114 73.36076
23 18.76580 73.35765
24 18.77090 73.36348
25 18.75822 73.37283
26 18.76368 73.38653
27 18.76939 73.40145
28 18.76301 73.41848
29 18.75766 73.42920
30 18.73973 73.42921
我想创建一个新的列(使用name route_str),其中包含通过在上述df
中为每行的上述数据框中加入所有纬度和纵向获得的字符串。例如,
> df$route_str[1] #should give
[1] "19.07597 72.87765, 19.06575 72.89918, 19.06331 72.91443,19.05159 72.93661..." so on till 30
我尝试了这个
> fun <- function(ip)
+ {
+ a <- ip[[1]]
+ a[3] <- paste(a[1],a[2]," ")
+ op <- paste(a[3],collapse = ",")
+ return(op)
+ }
> df$route_str <- lapply(df$route_line,fun)
但是我得到的输出是
> unique_routes$route_str[1]
[[1]]
[1] "19.0759696960449 19.0657501220703 "
我尝试使用以下代码创建可重复的数据,但结构并不相同
df <- data.frame(src=c("chennai","Mumbai","Bangalore"),dest=c("Mumbai","Bangalore","Mumbai"),route=list(list(lat=c(19,20,21),lon=c(72,73,74)),data.frame(lat=c(19,20,21),lon=c(72,73,74)),data.frame(lat=c(19,20,21),lon=c(72,73,74))))
但是上面创建的数据的结构如下
> str(df)
'data.frame': 3 obs. of 8 variables:
$ src : Factor w/ 3 levels "Bangalore","chennai",..: 2 3 1
$ dest : Factor w/ 2 levels "Bangalore","Mumbai": 2 1 2
$ route.lat : num 19 20 21
$ route.lon : num 72 73 74
$ route.lat.1: num 19 20 21
$ route.lon.1: num 72 73 74
$ route.lat.2: num 19 20 21
$ route.lon.2: num 72 73 74
我在Windows 10 PLS上使用R版本3.3.1帮助!
编辑:
这就是我最终获得复杂的数据框架的方式
初始数据框架就像这样
> df <- data.frame(source=c("chennai","Mumbai","Bangalore"),destination=c("Mumbai","Bangalore","Mumbai"))
> df
source destination
1 chennai Mumbai
2 Mumbai Bangalore
3 Bangalore Mumbai
我想在源和目的地之间包含一个包含所有路线(lat lon)的单字符串的列,由逗号分隔我使用Googleway软件包获取Waypoints
> library(googleway)
> res <- function(src,dest,key) #key is google maps API key
+ {
+ polylinex <- google_directions(origin = src,destination = dest,key = key)
+ return(polylinex$routes$overview_polyline$points)
+ }
> df$source <- as.character(df$source)
> df$destination <- as.character(df$destination)
> df$x <- mapply(res,df$source,df$destination,key)
> df$route_line <- lapply(df$x,function(y) googleway::decode_pl(y))
> df <- df[,!(names(df)=="x")]
> str(df)
'data.frame': 3 obs. of 3 variables:
$ source : chr "chennai" "Mumbai" "Bangalore"
$ destination: chr "Mumbai" "Bangalore" "Mumbai"
$ route_line :List of 3
..$ :'data.frame': 219 obs. of 2 variables:
.. ..$ lat: num 13.1 13.1 13.1 13.1 13.1 ...
.. ..$ lon: num 80.3 80.2 80.2 80.2 80.2 ...
..$ :'data.frame': 219 obs. of 2 variables:
.. ..$ lat: num 19.1 19.1 19.1 19.1 19.1 ...
.. ..$ lon: num 72.9 72.9 72.9 72.9 73 ...
..$ :'data.frame': 218 obs. of 2 variables:
.. ..$ lat: num 13 13 13 13 13 ...
.. ..$ lon: num 77.6 77.6 77.6 77.6 77.5 ...
对lapply
进行稍微修改为sapply
,然后稍微更改paste
序列将使您想要您想要
df$route_str <- sapply(df$x, function(y){
df_coords <- decode_pl(y)
paste0(t(sapply(df_coords, paste0)), collapse = ",")
})
str(df)
'data.frame': 3 obs. of 4 variables:
$ source : chr "chennai" "Mumbai" "Bangalore"
$ destination: chr "Mumbai" "Bangalore" "Mumbai"
$ x : chr "weznA{z|hNjrAlkDue@vsDtVnhD|dAnkErSbdI~kGzmRtmLjrNldI|iWnjBbuDf^duJgPzqNsiCtaIyLpnOyXzrKe{AvaG|JxpF~VpkCga@tkG_sBp|Cev@fvDpI|gF"| __truncated__ "ywlsBi|x{Lz~@qeCfNi~AfhAsiC}bBoiHpEu}Er~Cgu@znB_bB}~AohEvbGeyIp|A}|AzdC}aAnrB|DhjBo{@h}DujFfnIq_F`dDubFp}Bm{Af~Bs|DzTsaB`e@uy@w"| __truncated__ "oodnA}drxMkcAhKggApm@s}A|uAey@|rAi~BdjF{fDpaLgxB||F}`DvxE{sDdmDgkGthKmlK|vJmgIbzJa`BrjCssC|aBw`Dvw@osBrkCutNpbIigD|sCk`Ft_C}iPv"| __truncated__
$ route_str : chr "13.0826797485352,80.2706985473633,13.0693397521973,80.2431106567383,13.0755300521851,80.2141876220703,13.0717391967773,80.18706"| __truncated__ "19.0759696960449,72.8776473999023,19.0657501220703,72.8991775512695,19.0633087158203,72.9144287109375,19.0515899658203,72.93660"| __truncated__ "12.9715995788574,77.5945510864258,12.9825401306152,77.5925750732422,12.9940996170044,77.5851287841797,13.0092391967773,77.57122"| __truncated__
注意:我是googleway
作者,感谢您使用软件包