When I read the csv file into df, SoftwareOwner is a character column
> df
Software SoftwareOwner
<chr> <chr>
1 I-DEAS Siemens
2 TeamViewer Autodesk, TeamViewer, Siemens
3 Inventor PTC, Google, SpaceClaim, Bricys
4 AutoCAD Autodesk
I want to make SoftwareOwner a list within this data frame so I tried the simple solution
> df$SoftwareOwner <- as.list(df$SoftwareOwner)
But all this did was make each entry in the column a list with one entry
> df$SoftwareOwner[2]
[[1]]
[1] "Autodesk, TeamViewer, Siemens"
I've tried adding parameters like sep = "," and all.names = TRUE to as.list but neither worked. Is there any way to access just Autodesk or TeamViewer or Siemens when calling something like what I have just above?
Might I recommend making Siemens, Autodesk, Teamviewer, etc. their own columns and coding a 1 or 0 to indicate ownership? In my experience this is a far more flexible approach.
A possible solution :
# recreate your data.frame
df <- read.csv(text=
"Software;SoftwareOwner
I-DEAS;Siemens
TeamViewer;Autodesk, TeamViewer, Siemens
Inventor;PTC, Google, SpaceClaim, Bricys
AutoCAD;Autodesk",sep=";")
df$SoftwareOwner <- lapply(strsplit(as.character(df$SoftwareOwner),split=','),trimws)
# > df$SoftwareOwner
# [[1]]
# [1] "Siemens"
#
# [[2]]
# [1] "Autodesk" "TeamViewer" "Siemens"
#
# [[3]]
# [1] "PTC" "Google" "SpaceClaim" "Bricys"
#
# [[4]]
# [1] "Autodesk"
# > df$SoftwareOwner[[2]][3]
# [1] "Siemens"
# > df$SoftwareOwner[[3]][2]
# [1] "Google"
Related
I'm working on a shiny app which plots data trees. I'm looking to incorporate the shinyTree app to permit quick comparison of plotted nodes. The issue is that the shinyTree app returns a redundant list of lists of the sub node plot.
The actual list of list is included below. I would like to keep the longest branches only. I would also like to remove the id node (integer node), I'm struggling as to why it even shows up based on the list. I have tried many different methods to work with this list but it's been a real struggle. The list concept is difficult to understand.
I create the data.tree and plot via:
dataTree.a <- FromListSimple(checkList)
plot(dataTree.a)
> checkList
[[1]]
[[1]]$Asia
[[1]]$Asia$China
[[1]]$Asia$China$Beijing
[[1]]$Asia$China$Beijing$Round
[[1]]$Asia$China$Beijing$Round$`20383994`
[1] 0
[[2]]
[[2]]$Asia
[[2]]$Asia$China
[[2]]$Asia$China$Beijing
[[2]]$Asia$China$Beijing$Round
[1] 0
[[3]]
[[3]]$Asia
[[3]]$Asia$China
[[3]]$Asia$China$Beijing
[1] 0
[[4]]
[[4]]$Asia
[[4]]$Asia$China
[[4]]$Asia$China$Shanghai
[[4]]$Asia$China$Shanghai$Round
[[4]]$Asia$China$Shanghai$Round$`23740778`
[1] 0
[[5]]
[[5]]$Asia
[[5]]$Asia$China
[[5]]$Asia$China$Shanghai
[[5]]$Asia$China$Shanghai$Round
[1] 0
[[6]]
[[6]]$Asia
[[6]]$Asia$China
[[6]]$Asia$China$Shanghai
[1] 0
[[7]]
[[7]]$Asia
[[7]]$Asia$China
[1] 0
[[8]]
[[8]]$Asia
[[8]]$Asia$India
[[8]]$Asia$India$Delhi
[[8]]$Asia$India$Delhi$Round
[[8]]$Asia$India$Delhi$Round$`25703168`
[1] 0
[[9]]
[[9]]$Asia
[[9]]$Asia$India
[[9]]$Asia$India$Delhi
[[9]]$Asia$India$Delhi$Round
[1] 0
[[10]]
[[10]]$Asia
[[10]]$Asia$India
[[10]]$Asia$India$Delhi
[1] 0
[[11]]
[[11]]$Asia
[[11]]$Asia$India
[1] 0
[[12]]
[[12]]$Asia
[[12]]$Asia$Japan
[[12]]$Asia$Japan$Tokyo
[[12]]$Asia$Japan$Tokyo$Round
[[12]]$Asia$Japan$Tokyo$Round$`38001000`
[1] 0
[[13]]
[[13]]$Asia
[[13]]$Asia$Japan
[[13]]$Asia$Japan$Tokyo
[[13]]$Asia$Japan$Tokyo$Round
[1] 0
[[14]]
[[14]]$Asia
[[14]]$Asia$Japan
[[14]]$Asia$Japan$Tokyo
[1] 0
[[15]]
[[15]]$Asia
[[15]]$Asia$Japan
[1] 0
[[16]]
[[16]]$Asia
[1] 0
Well, I did cobble together a poor hack to make this work here is what I did to the 'checkList' list
checkList <- get_selected(tree, format = "slices")
# Convert and collapse shinyTree slices to data.tree
# This is a bit of a cluge to work the graphic with
# shinyTree an alternate one liner is in works
# This transform works by finding the longest branches
# and only plotting them since the other branches are
# subsets due to the slices.
# Extract the checkList name (as characters) from the checkList
tmp <- names(unlist(checkList))
# Determine the length of the individual checkList Names
lens <- lapply(tmp, function(x) length(strsplit(x, ".", fixed=TRUE)[[1]]))
# Find the elements with the highest length returns a list of high vals
lens.max <- which(lens == max(sapply(lens, max)))
# Replace all '.' with '\' prepping for DataFrameTable Converions
tmp <- relist(str_replace_all(tmp, "\\.", "/"), skeleton=tmp)
# Add a root node to work with multiple branches
tmp <- unlist(lapply(tmp, function(x) paste0("Root/", x)))
# Create a list of only the longest branches
longBranches <- as.list(tmp[lens.max])
# Convert the list into a data.frame for convert
longBranches.df <- data.frame(pathString = do.call(rbind, longBranches))
# Publish the data.frame for use
vals$selDF <- longBranches.df
#save(checkList, file = "chkLists.RData") # Save for troubleshooting
print(vals$selDF)ode here
The new checkList looks like this:
[1] "Root/Europe/France/Paris/Round/10843285" "Root/Europe/France/Paris/Round"
[3] "Root/Europe/France/Paris" "Root/Europe/France"
[5] "Root/Europe/Germany/Berlin/Diamond/3563194" "Root/Europe/Germany/Berlin/Diamond"
[7] "Root/Europe/Germany/Berlin/Round/3563194" "Root/Europe/Germany/Berlin/Round"
[9] "Root/Europe/Germany/Berlin" "Root/Europe/Germany"
[11] "Root/Europe/Italy/Rome/Round/3717956" "Root/Europe/Italy/Rome/Round"
[13] "Root/Europe/Italy/Rome" "Root/Europe/Italy"
[15] "Root/Europe/United Kingdom/London/Round/10313307" "Root/Europe/United Kingdom/London/Round"
[17] "Root/Europe/United Kingdom/London" "Root/Europe/United Kingdom"
[19] "Root/Europe"
It works :)... but I think this could be done with a two liner.... I'll work on it again in a week or so. Any other Ideas would be appreciated.
I have a list and the field inside each list element is of same name(only values are different) and I need to convert that into a data.frame with column name is same as that of field name. Following is my list,
Data input (data input in json format.json)
library(rjson)
data <- fromJSON(file = "data input in json format.json")
head(data,3)
[[1]]
[[1]]$floors
[1] 5
[[1]]$elevation
[1] 15
[[1]]$bmi
[1] 23.7483
[[2]]
[[2]]$floors
[1] 4
[[2]]$elevation
[1] 12
[[2]]$bmi
[1] 23.764
[[3]]
[[3]]$floors
[1] 3
[[3]]$elevation
[1] 9
[[3]]$bmi
[1] 23.7797
And my expected data.frame is,
floors elevation bmi
5 15 23.7483
4 12 23.7640
3 9 23.7797
Can you help me to figure out this ?.
Thanks in adavance.
You can use jsonlite.
library(jsonlite)
Then use fromJSON() and specify the path to your file (or alternatively a URL or the raw text) in the argument txt:
fromJSON(txt = 'path/to/json/file.json')
The result is:
floors elevation bmi
1 5 15 23.7483
2 4 12 23.7640
3 3 9 23.7797
If you prefer rjson, you could first read it as previously:
data <- rjson::fromJSON(file = 'path/to/json/file.json')
Then use do.call() and rbind.data.frame() to convert the list to a dataframe:
do.call("rbind.data.frame", data)
Alternatively to do.call(): use data.tables rbindlist() which is faster:
data.table::rbindlist(data)
I am writing my bachelor thesis and I have not much experience with r so far.
My problem is that my dates which I made with this commands :
t<-strptime(x, "%d.%m.%Y %H.%M")
don't work anymore when I save them in a matrix with the other information on those specific dates.
I am a bit confused because it works just fine when I don't put them in a matrix like this t[1:10]
But that happens as soon as I try to save them in a matrix
matrix1<-matrix(c(t,v2,v3,v4),nrow=length(v2))
Fehler in as.POSIXct.numeric(X[[i]], ...) : 'origin' muss angegeben werden
It's German but it means origin must be supplied.
Any ideas what I have to do to fix it? I am a bit frustrated :)
Roland is right. You can't have Posixlt objects in a matrix. What you can do is save those dates as numeric timestamps in the matrix and convert them back to dates while accessing
Converting to numeric timestamp:
>date<- as.numeric(as.POSIXct("2014-02-16 2:13:46 UTC",origin="01-01-1970"))
>date
[1] 1392545626
Then save those timestamps in a matrix as you do and to convert it back to date, use the above command again without converting it into a numeric.
t (terrible name by the way, easily confused with the t function) is a POSIXlt object, which internally is a list. First you should check, what c(t,v2,v3,v4) returns (I don't know how v2 etc are defined).
Then we can look into the documentation in help("matrix"):
data
an optional data vector (including a list or expression vector). Non-atomic classed R objects are coerced by as.vector and all attributes discarded.
The important bit is "all attributes discarded". This is what you get if you discard the attributes (which include the class attribute) of a POSIXlt object:
x <- strptime(c("2016-05-09 12:00:00", "2016-05-09 13:00:00"), format = "%Y-%m-%d %H:%M:%S")
attributes(x) <- NULL
print(x)
# [[1]]
# [1] 0 0
#
# [[2]]
# [1] 0 0
#
# [[3]]
# [1] 12 13
#
# [[4]]
# [1] 9 9
#
# [[5]]
# [1] 4 4
#
# [[6]]
# [1] 116 116
#
# [[7]]
# [1] 1 1
#
# [[8]]
# [1] 129 129
#
# [[9]]
# [1] 1 1
#
# [[10]]
# [1] "CEST" "CEST"
#
# [[11]]
# [1] NA NA
A matrix can't contain POSIXlt objects (or any objects, i.e., anything with an explicit class).
This is the second time that I have faced this recently, so I wanted to reach out to see if there is a better way to parse dataframes returned from jsonlite when one of elements is an array stored as a column in the dataframe as a list.
I know that this part of the power with jsonlite, but I am not sure how to work with this nested structure. In the end, I suppose that I can write my own custom parsing, but given that I am almost there, I wanted to see how to work with this data.
For example:
## options
options(stringsAsFactors=F)
## packages
library(httr)
library(jsonlite)
## setup
gameid="2015020759"
SEASON = '20152016'
BASE = "http://live.nhl.com/GameData/"
URL = paste0(BASE, SEASON, "/", gameid, "/PlayByPlay.json")
## get the data
x <- GET(URL)
## parse
api_response <- content(x, as="text")
api_response <- jsonlite::fromJSON(api_response, flatten=TRUE)
## get the data of interest
pbp <- api_response$data$game$plays$play
colnames(pbp)
And exploring what comes back:
> class(pbp$aoi)
[1] "list"
> class(pbp$desc)
[1] "character"
> class(pbp$xcoord)
[1] "integer"
From above, the column pbp$aoi is a list. Here are a few entries:
> head(pbp$aoi)
[[1]]
[1] 8465009 8470638 8471695 8473419 8475792 8475902
[[2]]
[1] 8470626 8471276 8471695 8476525 8476792 8477956
[[3]]
[1] 8469619 8471695 8473492 8474625 8475727 8476525
[[4]]
[1] 8469619 8471695 8473492 8474625 8475727 8476525
[[5]]
[1] 8469619 8471695 8473492 8474625 8475727 8476525
[[6]]
[1] 8469619 8471695 8473492 8474625 8475727 8475902
I don't really care if I parse these lists in the same dataframe, but what do I have for options to parse out the data?
I would prefer to take the data out of out lists and parse them into a dataframe that can be "related" to the original record it came from.
Thanks in advance for your help.
From #hrbmstr above, I was able to get what I wanted using unnest.
select(pbp, eventid, aoi) %>% unnest() %>% head
How would I load data from a csv file into R if the file contains different numbers of strings in every line? I need to unite it in one variable (E.g. a list of lists?). The data in the file looks like this (I don't know the maximum number of elements in one row):
Peter; Paul; Mary
Jeff;
Peter; Jeff
Julia; Vanessa; Paul
Use fill=TRUE:
read.table(text='
Peter; Paul; Mary
Jeff;
Peter; Jeff
Julia; Vanessa; Paul',sep=';',fill=TRUE)
V1 V2 V3
1 Peter Paul Mary
2 Jeff
3 Peter Jeff
4 Julia Vanessa Paul
r <- readLines("tmp3.csv")
getLine <- function(x) {
r <- scan(text=x,sep=";",what="character",quiet=TRUE)
r <- r[nchar(r)>0] ## drop empties
r <- gsub("(^ +| +$)","",r) ## strip whitespace
r
}
lapply(r,getLine)
## [[1]]
## [1] "Peter" "Paul" "Mary"
##
## [[2]]
## [1] "Jeff"
##
## [[3]]
## [1] "Peter" "Jeff"
##
## [[4]]
## [1] "Julia" "Vanessa" "Paul"
This is technically a list of vectors rather than a list of lists but it might be what you want ...