How to use a list of row numbers to look up values in a dataframe column
Question
I have a big dataframe containing to columns, one that is an ID Code named "code" and one that is the name of two train stations separated by a slash named "name"
I wanted to search all the codes associated to a station name (and being able to lookup multiple stations at a time) so it would give me a list of vectors containing the multiple codes for each station.
I used lapply to get the rows for each station but now I'm unable to look up the value in the column "code" associated with the row number.
SearchFor <- c("Chicago", "New York", "Atlanta")
lapply(c(SearchFor,grep,x=datastations$name)
I have the following list:
$`Chicago`
[1] 29 64 135 160 164 167 176 186 225 247 248
$New York
[1] 51 53 109 111 112 164
$Atlanta
[1] 4 78 168 237 291
Basically, I'd want to change each of these numbers into the value of the column "code" at these rows.
Here's my datatable "datastations" after I used dput:
structure(list(code = c(6000L, 6001L, 6002L, 6003L, 6004L, 6005L,
6006L, 6007L, 6008L, 6009L, 6010L, 6011L, 6012L, 6013L, 6014L,
6015L, 6016L, 6017L, 6018L, 6019L, 6020L, 6021L, 6022L, 6023L,
6024L, 6025L, 6026L, 6027L, 6028L, 6029L, 6030L, 6031L, 6032L,
6033L, 6034L, 6035L, 6036L, 6037L, 6038L, 6039L, 6040L, 6041L,
6042L, 6043L, 6044L, 6045L, 6046L, 6047L, 6048L, 6049L, 5000L,
5001L, 5002L, 5003L, 5004L, 5005L, 5006L, 5007L, 5008L, 6050L,
6051L, 6052L, 6053L, 6054L, 6055L, 6056L, 6057L, 6058L, 6059L,
6060L, 6061L, 6062L, 6063L, 6064L, 6065L, 6066L, 6067L, 6068L,
6069L, 6070L, 6071L, 6072L, 6073L, 6074L, 6075L, 6076L, 6077L,
6078L, 6079L, 6080L, 6081L, 6082L, 6083L, 6084L, 6085L, 6086L,
6087L, 6088L, 6089L, 6090L, 6091L, 5009L, 5010L, 5011L, 5012L,
6092L, 6093L, 6094L, 6095L, 6096L, 6097L), name = c("Atlanta / New York",
"Atlanta / Chicago", "Atlanta / Miami", "Atlanta / Los Angeles",
"Atlanta / Toronto", "Atlanta / Washington", "Atlanta / Cleveland",
"Atlanta / Raleigh", "Atlanta / Newark", "Atlanta / Ottawa",
"Atlanta / Detroit", "Atlanta / Albany", "Atlanta / Hartford",
"Atlanta / Providence", "New York / Chicago", "New York / Miami",
"New York / Los Angeles", "New York / Toronto", "New York / Washington",
"New York / Cleveland", "New York / Raleigh", "New York / Newark",
"New York / Ottawa", "New York / Detroit", "New York / Albany",
"New York / Hartford", "New York / Providence", "Chicago / Miami",
"Chicago / Los Angeles", "Chicago / Toronto", "Chicago / Washington",
"Chicago / Cleveland", "Chicago / Raleigh", "Chicago / Newark",
"Chicago / Ottawa", "Chicago / Detroit", "Chicago / Albany",
"Chicago / Hartford", "Chicago / Providence", "Miami / Los Angeles",
"Miami / Toronto", "Miami / Washington", "Miami / Cleveland",
"Miami / Raleigh", "Miami / Newark", "Miami / Ottawa", "Miami / Detroit",
"Miami / Albany", "Miami / Hartford", "Miami / Providence", "Toronto / Washington",
"Toronto / Cleveland", "Toronto / Raleigh", "Toronto / Newark",
"Toronto / Ottawa", "Toronto / Detroit", "Toronto / Albany",
"Toronto / Hartford", "Toronto / Providence", "Los Angeles / Toronto",
"Los Angeles / Washington", "Los Angeles / Cleveland", "Los Angeles / Raleigh",
"Los Angeles / Newark", "Los Angeles / Ottawa", "Los Angeles / Detroit",
"Los Angeles / Albany", "Los Angeles / Hartford", "Los Angeles / Providence",
"Washington / Washington", "Washington / Cleveland", "Washington / Raleigh",
"Washington / Newark", "Washington / Ottawa", "Washington / Detroit",
"Washington / Hartford", "Washington / Providence", "Raleigh / Newark",
"Raleigh / Ottawa", "Raleigh / Detroit", "Raleigh / Albany",
"Raleigh / Hartford", "Raleigh / Providence", "Cleveland / Raleigh",
"Cleveland / Newark", "Cleveland / Ottawa", "Cleveland / Detroit",
"Cleveland / Albany", "Cleveland / Hartford", "Cleveland / Providence",
"New York / Newark", "New York / Ottawa", "New York / Detroit",
"New York / Albany", "New York / Hartford", "New York / Providence",
"Newark / Ottawa", "Newark / Detroit", "Newark / Albany", "Newark / Hartford",
"Newark / Providence", "Ottawa / Detroit", "Ottawa / Albany",
"Ottawa / Hartford", "Ottawa / Providence", "Detroit / Albany",
"Detroit / Hartford", "Detroit / Providence", "Albany / Hartford",
"Albany / Providence", "Hartford / Providence")), class = "data.frame", row.names = c(NA,
-111L))
I got this database by reading a .csv file using this code
read.csv(file, colClasses =
c(rep("integer",1),rep("character",1),rep("NULL",2)))
I'd like to apply something like :
List[1] <- datastations$code[List[[1]]]
but on every vector of the list, no matter how many there are (so no loop basically)
2 answers
solution1
0 2018-10-14 03:30:25
Maybe this is what you're looking for? The way I read the question, you need a list of all the station codes that correspond to a particular city or group of cities. It looks like maybe the wrong station codes got in your dput if this looks funny.
library(dplyr)
codelist <- df %>% filter(grepl("Chicago",name)) %>% select(code)
> unlist(codelist)
code1 code2 code3 code4 code5 code6 code7 code8 code9 code10 code11 code12 code13 code14
6001 6014 6027 6028 6029 6030 6031 6032 6033 6034 6035 6036 6037 6038
Or for multiple stations:
> codelist <- df %>% filter(grepl("Chicago|New York|Atlanta",name)) %>% select(code)
> unlist(codelist)
code1 code2 code3 code4 code5 code6 code7 code8 code9 code10 code11 code12 code13 code14 code15
6000 6001 6002 6003 6004 6005 6006 6007 6008 6009 6010 6011 6012 6013 6014
code16 code17 code18 code19 code20 code21 code22 code23 code24 code25 code26 code27 code28 code29 code30
6015 6016 6017 6018 6019 6020 6021 6022 6023 6024 6025 6026 6027 6028 6029
code31 code32 code33 code34 code35 code36 code37 code38 code39 code40 code41 code42 code43 code44 code45
6030 6031 6032 6033 6034 6035 6036 6037 6038 6081 6082 6083 6084 6085 6086
solution2
0 ACCPTED 2018-10-14 08:05:58
Like others have said in comments above, it's not entirely clear what the end result is that you want. But if I understand correctly, I think this might be what you want.
Here I'm using map from the package purrr to iterate over a vector of city names and get a vector of codes for each one, the use set_names to name the elements of the final list by the cities.
library(dplyr)
library(stringr)
library(purrr)
# load data as df (see below)
cities <- c("Chicago", "New York", "Atlanta")
get_city_stations <- function(city, station_data) {
station_data %>%
filter(str_detect(name, city)) %>%
pull(code)
}
codes <- map(cities, get_city_stations, station_data = df) %>% set_names(cities)
codes
#> $Chicago
#> [1] 6001 6014 6027 6028 6029 6030 6031 6032 6033 6034 6035 6036 6037 6038
#>
#> $`New York`
#> [1] 6000 6014 6015 6016 6017 6018 6019 6020 6021 6022 6023 6024 6025 6026
#> [15] 6081 6082 6083 6084 6085 6086
#>
#> $Atlanta
#> [1] 6000 6001 6002 6003 6004 6005 6006 6007 6008 6009 6010 6011 6012 6013
Created on 2018-10-14 by the reprex package (v0.2.0).
df <- structure(list(code = c(6000L, 6001L, 6002L, 6003L, 6004L, 6005L,
6006L, 6007L, 6008L, 6009L, 6010L, 6011L, 6012L, 6013L, 6014L,
6015L, 6016L, 6017L, 6018L, 6019L, 6020L, 6021L, 6022L, 6023L,
6024L, 6025L, 6026L, 6027L, 6028L, 6029L, 6030L, 6031L, 6032L,
6033L, 6034L, 6035L, 6036L, 6037L, 6038L, 6039L, 6040L, 6041L,
6042L, 6043L, 6044L, 6045L, 6046L, 6047L, 6048L, 6049L, 5000L,
5001L, 5002L, 5003L, 5004L, 5005L, 5006L, 5007L, 5008L, 6050L,
6051L, 6052L, 6053L, 6054L, 6055L, 6056L, 6057L, 6058L, 6059L,
6060L, 6061L, 6062L, 6063L, 6064L, 6065L, 6066L, 6067L, 6068L,
6069L, 6070L, 6071L, 6072L, 6073L, 6074L, 6075L, 6076L, 6077L,
6078L, 6079L, 6080L, 6081L, 6082L, 6083L, 6084L, 6085L, 6086L,
6087L, 6088L, 6089L, 6090L, 6091L, 5009L, 5010L, 5011L, 5012L,
6092L, 6093L, 6094L, 6095L, 6096L, 6097L), name = c("Atlanta / New York",
"Atlanta / Chicago", "Atlanta / Miami", "Atlanta / Los Angeles",
"Atlanta / Toronto", "Atlanta / Washington", "Atlanta / Cleveland",
"Atlanta / Raleigh", "Atlanta / Newark", "Atlanta / Ottawa",
"Atlanta / Detroit", "Atlanta / Albany", "Atlanta / Hartford",
"Atlanta / Providence", "New York / Chicago", "New York / Miami",
"New York / Los Angeles", "New York / Toronto", "New York / Washington",
"New York / Cleveland", "New York / Raleigh", "New York / Newark",
"New York / Ottawa", "New York / Detroit", "New York / Albany",
"New York / Hartford", "New York / Providence", "Chicago / Miami",
"Chicago / Los Angeles", "Chicago / Toronto", "Chicago / Washington",
"Chicago / Cleveland", "Chicago / Raleigh", "Chicago / Newark",
"Chicago / Ottawa", "Chicago / Detroit", "Chicago / Albany",
"Chicago / Hartford", "Chicago / Providence", "Miami / Los Angeles",
"Miami / Toronto", "Miami / Washington", "Miami / Cleveland",
"Miami / Raleigh", "Miami / Newark", "Miami / Ottawa", "Miami / Detroit",
"Miami / Albany", "Miami / Hartford", "Miami / Providence", "Toronto / Washington",
"Toronto / Cleveland", "Toronto / Raleigh", "Toronto / Newark",
"Toronto / Ottawa", "Toronto / Detroit", "Toronto / Albany",
"Toronto / Hartford", "Toronto / Providence", "Los Angeles / Toronto",
"Los Angeles / Washington", "Los Angeles / Cleveland", "Los Angeles / Raleigh",
"Los Angeles / Newark", "Los Angeles / Ottawa", "Los Angeles / Detroit",
"Los Angeles / Albany", "Los Angeles / Hartford", "Los Angeles / Providence",
"Washington / Washington", "Washington / Cleveland", "Washington / Raleigh",
"Washington / Newark", "Washington / Ottawa", "Washington / Detroit",
"Washington / Hartford", "Washington / Providence", "Raleigh / Newark",
"Raleigh / Ottawa", "Raleigh / Detroit", "Raleigh / Albany",
"Raleigh / Hartford", "Raleigh / Providence", "Cleveland / Raleigh",
"Cleveland / Newark", "Cleveland / Ottawa", "Cleveland / Detroit",
"Cleveland / Albany", "Cleveland / Hartford", "Cleveland / Providence",
"New York / Newark", "New York / Ottawa", "New York / Detroit",
"New York / Albany", "New York / Hartford", "New York / Providence",
"Newark / Ottawa", "Newark / Detroit", "Newark / Albany", "Newark / Hartford",
"Newark / Providence", "Ottawa / Detroit", "Ottawa / Albany",
"Ottawa / Hartford", "Ottawa / Providence", "Detroit / Albany",
"Detroit / Hartford", "Detroit / Providence", "Albany / Hartford",
"Albany / Providence", "Hartford / Providence")), class = "data.frame", row.names = c(NA,
-111L))
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