r - Write.table as text file with differing number of rows -
i want share output of analysis in r txt file. can 1 here know of:
write.table(s$maininformation, file = "output.txt", row.names = false, sep = "\t", quote = false, fileencoding = "utf-8", append = true) write.table(s$annualproduction, file = "output.txt", row.names = false, sep = "\t", quote = false, fileencoding = "utf-8", append = true) write.table(s$annualgrowthrate, file = "output.txt", row.names = false, sep = "\t", quote = false, fileencoding = "utf-8", append = true) write.table(s$mostprodauthors, file = "output.txt", row.names = false, sep = "\t", quote = false, fileencoding = "utf-8", append = true) the documents combined 1 txt file. however, if want in 1 step, i.e. s rather s$, error code, not surprisingly, argumetns imply differing number of rows.
write.table(s, file = "output.txt", row.names = false, sep = "\t", quote = false, fileencoding = "utf-8") error in (function (..., row.names = null, check.rows = false, check.names = true, : arguments imply differing number of rows: 16, 25, 1, 10
of course, don't care that... don't know yet how work lapply helpful_ thanks! scw
str(s) list of 9 $ maininformation : chr [1:16] "\n\nmain information data\n\n" "articles 1374 \n" "sources (journals, books, etc.) 736 \n" "keywords plus (id) 1172 \n" ... $ annualproduction :'data.frame': 25 obs. of 2 variables: ..$ year : factor w/ 25 levels "1985","1988",..: 1 2 3 4 5 6 7 8 9 10 ... ..$ articles: int [1:25] 1 1 1 1 3 1 2 2 3 2 ... $ annualgrowthrate : num 20.9 $ mostprodauthors :'data.frame': 10 obs. of 4 variables: ..$ authors :class 'asis' chr [1:10] "nye,j. " "grix,j " "ogunnubi,o " "pamment,j " ... ..$ articles :class 'asis' chr [1:10] "16" " 8" " 8" " 8" ... ..$ authors :class 'asis' chr [1:10] "nye,j. " "pamment,j " "chong,a " "lee,j " ... ..$ articles fractionalized:class 'asis' chr [1:10] "16.00" " 8.00" " 6.00" " 5.00" ... $ mostcitedpapers :'data.frame': 10 obs. of 3 variables: ..$ paper :class 'asis' chr [1:10] "santos f;eisenhardt k,(2009),acad. manage. j. " "hyde-price a,(2006),j. eur. public policy " "nye j.,(2008),ann. am. acad. polit. soc. sci. " "nye j.,(2003),the paradox of am. power: why world's superpower can't go alone" ... ..$ tc :class 'asis' chr [1:10] "262" "133" "120" "119" ... ..$ tcperyear :class 'asis' chr [1:10] "32.75" "12.09" "13.33" " 8.50" ... $ mostprodcountries:'data.frame': 10 obs. of 3 variables: ..$ country :class 'asis' chr [1:10] "usa " "england " "australia " "china " ... ..$ articles :class 'asis' chr [1:10] "255" " 96" " 81" " 67" ... ..$ freq :class 'asis' chr [1:10] "0.2621" "0.0987" "0.0832" "0.0689" ... $ tcpercountries :'data.frame': 10 obs. of 3 variables: ..$ country :class 'asis' chr [1:10] "usa " "england " "australia " "united kingdom" ... ..$ total citations :class 'asis' chr [1:10] "1701" " 708" " 303" " 297" ... ..$ average article citations: chr [1:10(1d)] "6.671" "7.375" "3.741" "6.319" ... .. ..- attr(*, "dimnames")=list of 1 .. .. ..$ co: chr [1:10] "usa" "england" "australia" "united kingdom" ... $ mostrelsources :'data.frame': 10 obs. of 2 variables: ..$ sources :class 'asis' chr [1:10] "international journal of history of sport " "international journal of communication " "international journal of cultural policy " "journal of contemporary china " ... ..$ articles :class 'asis' chr [1:10] "19" "16" "16" "14" ... $ mostrelkeywords :'data.frame': 10 obs. of 4 variables: ..$ author keywords (de) :class 'asis' chr [1:10] "soft power " "china " "public diplomacy " "foreign policy " ... ..$ articles :class 'asis' chr [1:10] "387" "119" " 74" " 50" ... ..$ keywords-plus (id) :class 'asis' chr [1:10] "soft power " "foreign policy " "politics " "china " ... ..$ articles :class 'asis' chr [1:10] "112" " 47" " 41" " 39" ...
is file meant human-readable or machine-readable?
if human-readable, capture.output() suggested above should sufficient.
lst <- list(a=1:8, b=1.2e+11, df1=data.frame(foo=1:5/4, bar=1:5/3), df2=as.data.frame(matrix(runif(16), 4))) capture.output(lst, file="list.txt") otherwise, if insist on putting things side-by side, might option
max_l <- max(rapply(lst, length)) as.data.frame(rapply(lst, function(x) 'length<-'(x, max_l), how="list")) # b df1.foo df1.bar df2.v1 df2.v2 df2.v3 df2.v4 # 1 1 1.2e+11 0.25 0.3333333 0.3978436 0.1971467 0.5619881 0.01103607 # 2 2 na 0.50 0.6666667 0.9556758 0.1153423 0.7327180 0.90631526 # 3 3 na 0.75 1.0000000 0.6533494 0.9959655 0.8708056 0.77065363 # 4 4 na 1.00 1.3333333 0.3287437 0.3792767 0.5721703 0.38250462 # 5 5 na 1.25 1.6666667 na na na na # 6 6 na na na na na na na # 7 7 na na na na na na na # 8 8 na na na na na na na and write file other data.frame.
if file meant machine-readable, maybe results further processed using other software, better approach use more specialized file format plain text. json or xml.
writing json simple as
library(rjsonio) write(tojson(lst), file="list.json") the resulting file still human-readable, think.
{ "a": [ 1, 2, 3, 4, 5, 6, 7, 8 ], "b": 1.2e+11, "df1": { "foo": [ 0.25, 0.5, 0.75, 1, 1.25 ], "bar": [ 0.33333, 0.66667, 1, 1.3333, 1.6667 ] }, "df2": { "v1": [ 0.094046, 0.049654, 0.82116, 0.82932 ], "v2": [ 0.65473, 0.13283, 0.34181, 0.73137 ], "v3": [ 0.90729, 0.6962, 0.24158, 0.64411 ], "v4": [ 0.28075, 0.95764, 0.1584, 0.41834 ] } }
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