Conversión de lista anidada a dataframe

El objective es convertir una lista anidada que a veces contiene registros faltantes en un dataframe. Un ejemplo de la estructura cuando faltan registros es:

str(mylist) List of 3 $ :List of 7 ..$ Hit : chr "True" ..$ Project: chr "Blue" ..$ Year : chr "2011" ..$ Rating : chr "4" ..$ Launch : chr "26 Jan 2012" ..$ ID : chr "19" ..$ Dept : chr "1, 2, 4" $ :List of 2 ..$ Hit : chr "False" ..$ Error: chr "Record not found" $ :List of 7 ..$ Hit : chr "True" ..$ Project: chr "Green" ..$ Year : chr "2004" ..$ Rating : chr "8" ..$ Launch : chr "29 Feb 2004" ..$ ID : chr "183" ..$ Dept : chr "6, 8" 

Cuando no faltan registros, la lista se puede convertir en un dataframe usando data.frame(do.call(rbind.data.frame, mylist)) . Sin embargo, cuando faltan registros, esto da como resultado una columna no coincidente. Sé que hay funciones para combinar marcos de datos de columnas que no coinciden, pero aún no he encontrado una que se pueda aplicar a las listas. El resultado ideal sería mantener el registro 2 con NA para todas las variables. Esperando algo de ayuda.

Editar para agregar dput(mylist) :

 list(structure(list(Hit = "True", Project = "Blue", Year = "2011", Rating = "4", Launch = "26 Jan 2012", ID = "19", Dept = "1, 2, 4"), .Names = c("Hit", "Project", "Year", "Rating", "Launch", "ID", "Dept")), structure(list( Hit = "False", Error = "Record not found"), .Names = c("Hit", "Error")), structure(list(Hit = "True", Project = "Green", Year = "2004", Rating = "8", Launch = "29 Feb 2004", ID = "183", Dept = "6, 8"), .Names = c("Hit", "Project", "Year", "Rating", "Launch", "ID", "Dept"))) 

También puede usar (al menos v1.9.3) de rbindlist en el paquete data.table :

 library(data.table) rbindlist(mylist, fill=TRUE) ## Hit Project Year Rating Launch ID Dept Error ## 1: True Blue 2011 4 26 Jan 2012 19 1, 2, 4 NA ## 2: False NA NA NA NA NA NA Record not found ## 3: True Green 2004 8 29 Feb 2004 183 6, 8 NA 

Puede crear una lista de data.frames:

 dfs <- lapply(mylist, data.frame, stringsAsFactors = FALSE) 

Luego usa uno de estos:

 library(plyr) rbind.fill(dfs) 

o el más rápido

 library(dplyr) rbind_all(dfs) 

En el caso de dplyr::rbind_all , me sorprende que elija usar "" lugar de NA para los datos faltantes. Si elimina stringsAsFactors = FALSE , obtendrá NA pero a costa de una advertencia ... Así que suppressWarnings(rbind_all(lapply(mylist, data.frame))) advertencias suppressWarnings(rbind_all(lapply(mylist, data.frame))) sería una solución fea pero rápida.

Acabo de desarrollar una solución para esta pregunta que es aplicable aquí, así que la proporcionaré aquí también:

 tl <- function(e) { if (is.null(e)) return(NULL); ret <- typeof(e); if (ret == 'list' && !is.null(names(e))) ret <- list(type='namedlist') else ret <- list(type=ret,len=length(e)); ret; }; mkcsv <- function(v) paste0(collapse=',',v); keyListToStr <- function(keyList) paste0(collapse='','/',sapply(keyList,function(key) if (is.null(key)) '*' else paste0(collapse=',',key))); extractLevelColumns <- function( nodes, ## current level node selection ..., ## additional arguments to data.frame() keyList=list(), ## current key path under main list sep=NULL, ## optional string separator on which to join multi-element vectors; if NULL, will leave as separate columns mkname=function(keyList,maxLen) paste0(collapse='.',if (is.null(sep) && maxLen == 1L) keyList[-length(keyList)] else keyList) ## name builder from current keyList and character vector max length across node level; default to dot-separated keys, and remove last index component for scalars ) { cat(sprintf('extractLevelColumns(): %s\n',keyListToStr(keyList))); if (length(nodes) == 0L) return(list()); ## handle corner case of empty main list tlList <- lapply(nodes,tl); typeList <- do.call(c,lapply(tlList,`[[`,'type')); if (length(unique(typeList)) != 1L) stop(sprintf('error: inconsistent types (%s) at %s.',mkcsv(typeList),keyListToStr(keyList))); type <- typeList[1L]; if (type == 'namedlist') { ## hash; recurse allKeys <- unique(do.call(c,lapply(nodes,names))); ret <- do.call(c,lapply(allKeys,function(key) extractLevelColumns(lapply(nodes,`[[`,key),...,keyList=c(keyList,key),sep=sep,mkname=mkname))); } else if (type == 'list') { ## array; recurse lenList <- do.call(c,lapply(tlList,`[[`,'len')); maxLen <- max(lenList,na.rm=T); allIndexes <- seq_len(maxLen); ret <- do.call(c,lapply(allIndexes,function(index) extractLevelColumns(lapply(nodes,function(node) if (length(node) < index) NULL else node[[index]]),...,keyList=c(keyList,index),sep=sep,mkname=mkname))); ## must be careful to translate out-of-bounds to NULL; happens automatically with string keys, but not with integer indexes } else if (type%in%c('raw','logical','integer','double','complex','character')) { ## atomic leaf node; build column lenList <- do.call(c,lapply(tlList,`[[`,'len')); maxLen <- max(lenList,na.rm=T); if (is.null(sep)) { ret <- lapply(seq_len(maxLen),function(i) setNames(data.frame(sapply(nodes,function(node) if (length(node) < i) NA else node[[i]]),...),mkname(c(keyList,i),maxLen))); } else { ## keep original type if maxLen is 1, IOW don't stringify ret <- list(setNames(data.frame(sapply(nodes,function(node) if (length(node) == 0L) NA else if (maxLen == 1L) node else paste(collapse=sep,node)),...),mkname(keyList,maxLen))); }; ## end if } else stop(sprintf('error: unsupported type %s at %s.',type,keyListToStr(keyList))); if (is.null(ret)) ret <- list(); ## handle corner case of exclusively empty sublists ret; }; ## end extractLevelColumns() ## simple interface function flattenList <- function(mainList,...) do.call(cbind,extractLevelColumns(mainList,...)); 

Ejecución:

 ## define data mylist <- list(structure(list(Hit='True',Project='Blue',Year='2011',Rating='4',Launch='26 Jan 2012',ID='19',Dept='1, 2, 4'),.Names=c('Hit','Project','Year','Rating','Launch','ID','Dept')),structure(list(Hit='False',Error='Record not found'),.Names=c('Hit','Error')),structure(list(Hit='True',Project='Green',Year='2004',Rating='8',Launch='29 Feb 2004',ID='183',Dept='6, 8'),.Names=c('Hit','Project','Year','Rating','Launch','ID','Dept'))); ## run it df <- flattenList(mylist); ## extractLevelColumns(): ## extractLevelColumns(): Hit ## extractLevelColumns(): Project ## extractLevelColumns(): Year ## extractLevelColumns(): Rating ## extractLevelColumns(): Launch ## extractLevelColumns(): ID ## extractLevelColumns(): Dept ## extractLevelColumns(): Error df; ## Hit Project Year Rating Launch ID Dept Error ## 1 True Blue 2011 4 26 Jan 2012 19 1, 2, 4  ## 2 False       Record not found ## 3 True Green 2004 8 29 Feb 2004 183 6, 8  

Mi función es más poderosa que data.table::rbindlist() desde 1.9.6, ya que puede manejar cualquier número de niveles de anidación y diferentes longitudes de vector en las twigs. En la pregunta vinculada, mi función aplana correctamente la lista del OP a un data.frame, pero data.table::rbindlist() falla con "Error in rbindlist(jsonRList, fill = T) : Column 4 of item 16 is length 2, inconsistent with first column of that item which is length 1. rbind/rbindlist doesn't recycle as it already expects each item to be a uniform list, data.frame or data.table" .