Merge list of data.frames retaining all rows
mergeAllXY(...)arguments are handled as described:
named arguments are passed through to base::merge.data.frame(),
with the exception of all.x and all.y which are both defined
all.x=TRUE and all.y=TRUE.
and all other arguments are assumed
to be data.frame or equivalent, and are merged in order they
appear as arguments. The order of these data.frame objects
should not affect the output content, but will affect the row
and column order of the resulting data.frame.
data.frame after iterative calls to base::merge.data.frame().
This function is a wrapper around base::merge.data.frame()
except that it allows more than two data.frame objects,
and applies default arguments all.x=TRUE and all.y=TRUE
for each merge operation to ensure that all rows are kept.
Other jam practical functions:
breakDensity(),
checkLightMode(),
check_pkg_installed(),
colNum2excelName(),
color_dither(),
diff_functions(),
exp2signed(),
fileInfo(),
fixYellow(),
getAxisLabel(),
handleArgsText(),
heads(),
isFALSEV(),
isTRUEV(),
jamba,
jargs(),
kable_coloring(),
lldf(),
log2signed(),
make_html_styles(),
make_styles(),
match_unique(),
middle(),
minorLogTicks(),
newestFile(),
printDebugI(),
printDebug(),
renameColumn(),
rmInfinite(),
rmNAs(),
rmNA(),
rmNULL(),
sclass(),
sdim(),
setPrompt()
Other jam list functions:
cPasteSU(),
cPasteS(),
cPasteUnique(),
cPasteU(),
cPaste(),
heads(),
jam_rapply(),
list2df(),
mixedSorts(),
rbindList(),
relist_named(),
rlengths(),
sclass(),
sdim(),
uniques(),
unnestList()
df1 <- data.frame(City=c("New York", "Los Angeles", "San Francisco"),
State=c("New York", "California", "California"))
df2 <- data.frame(Team=c("Yankees", "Mets", "Giants", "Dodgers"),
City=c("New York", "New York", "San Francisco", "Los Angeles"))
df3 <- data.frame(State=c("New York", "California"),
`State Population`=c(39.24e9, 8.468e9),
check.names=FALSE)
mergeAllXY(df1, df3, df2)
#> City State State Population Team
#> 1 Los Angeles California 8.468e+09 Dodgers
#> 2 New York New York 3.924e+10 Yankees
#> 3 New York New York 3.924e+10 Mets
#> 4 San Francisco California 8.468e+09 Giants
df4 <- data.frame(check.names=FALSE,
CellLine=rep(c("ul3", "dH1A", "dH1B"), each=2),
Treatment=c("Vehicle", "Dex"))
df4$CellLine <- factor(df4$CellLine,
levels=c("ul3", "dH1A", "dH1B"))
df4$Treatment <- factor(df4$Treatment,
levels=c("Vehicle", "Dex"))
df5 <- data.frame(
Treatment=rep(c("Vehicle", "Dex"), each=3),
Time=c("0h", "12h", "24h"))
df6 <- data.frame(check.names=FALSE,
CellLine=c("ul3", "dH1A", "dH1B"),
Type=c("Control", "KO", "KO"))
mergeAllXY(df4, df5, df6)
#> CellLine Treatment Time Type
#> 1 dH1A Dex 12h KO
#> 2 dH1A Dex 0h KO
#> 3 dH1A Vehicle 0h KO
#> 4 dH1A Dex 24h KO
#> 5 dH1A Vehicle 24h KO
#> 6 dH1A Vehicle 12h KO
#> 7 dH1B Dex 12h KO
#> 8 dH1B Dex 24h KO
#> 9 dH1B Dex 0h KO
#> 10 dH1B Vehicle 0h KO
#> 11 dH1B Vehicle 12h KO
#> 12 dH1B Vehicle 24h KO
#> 13 ul3 Dex 0h Control
#> 14 ul3 Dex 12h Control
#> 15 ul3 Dex 24h Control
#> 16 ul3 Vehicle 24h Control
#> 17 ul3 Vehicle 0h Control
#> 18 ul3 Vehicle 12h Control
# note the factor order is maintained
mergeAllXY(df4, df5, df6)$CellLine
#> [1] dH1A dH1A dH1A dH1A dH1A dH1A dH1B dH1B dH1B dH1B dH1B dH1B ul3 ul3 ul3
#> [16] ul3 ul3 ul3
#> Levels: ul3 dH1A dH1B
mergeAllXY(df4, df5)$Treatment
#> [1] Dex Dex Dex Dex Dex Dex Dex Dex Dex
#> [10] Vehicle Vehicle Vehicle Vehicle Vehicle Vehicle Vehicle Vehicle Vehicle
#> Levels: Vehicle Dex
# merge "all" can append rows to a data.frame
df4b <- data.frame(check.names=FALSE,
CellLine=rep("dH1C", 2),
Treatment=c("Vehicle", "Dex"))
mergeAllXY(df4, df4b)
#> CellLine Treatment
#> 1 ul3 Vehicle
#> 2 ul3 Dex
#> 3 dH1A Vehicle
#> 4 dH1A Dex
#> 5 dH1B Vehicle
#> 6 dH1B Dex
#> 7 dH1C Vehicle
#> 8 dH1C Dex
# factor order is maintained, new levels are appended
mergeAllXY(df4, df4b)$CellLine
#> [1] ul3 ul3 dH1A dH1A dH1B dH1B dH1C dH1C
#> Levels: ul3 dH1A dH1B dH1C
# merge proceeds except shows missing data
mergeAllXY(df4, df4b, df5, df6)
#> CellLine Treatment Time Type
#> 1 ul3 Dex 0h Control
#> 2 ul3 Vehicle 0h Control
#> 3 ul3 Dex 12h Control
#> 4 ul3 Dex 24h Control
#> 5 ul3 Vehicle 12h Control
#> 6 ul3 Vehicle 24h Control
#> 7 dH1A Dex 12h KO
#> 8 dH1A Dex 0h KO
#> 9 dH1A Vehicle 12h KO
#> 10 dH1A Vehicle 0h KO
#> 11 dH1A Dex 24h KO
#> 12 dH1A Vehicle 24h KO
#> 13 dH1B Dex 24h KO
#> 14 dH1B Dex 0h KO
#> 15 dH1B Dex 12h KO
#> 16 dH1B Vehicle 24h KO
#> 17 dH1B Vehicle 0h KO
#> 18 dH1B Vehicle 12h KO
#> 19 dH1C Dex 0h <NA>
#> 20 dH1C Dex 12h <NA>
#> 21 dH1C Dex 24h <NA>
#> 22 dH1C Vehicle 0h <NA>
#> 23 dH1C Vehicle 12h <NA>
#> 24 dH1C Vehicle 24h <NA>
# note that appending rows is tricky, the following is incorrect
df6b <- data.frame(check.names=FALSE,
CellLine="dH1C",
Type="KO")
mergeAllXY(df4, df4b, df5, df6, df6b)
#> CellLine Type Treatment Time
#> 1 ul3 Control Dex 0h
#> 2 ul3 Control Vehicle 0h
#> 3 ul3 Control Dex 12h
#> 4 ul3 Control Dex 24h
#> 5 ul3 Control Vehicle 12h
#> 6 ul3 Control Vehicle 24h
#> 7 dH1A KO Dex 12h
#> 8 dH1A KO Dex 0h
#> 9 dH1A KO Vehicle 12h
#> 10 dH1A KO Vehicle 0h
#> 11 dH1A KO Dex 24h
#> 12 dH1A KO Vehicle 24h
#> 13 dH1B KO Dex 24h
#> 14 dH1B KO Dex 0h
#> 15 dH1B KO Dex 12h
#> 16 dH1B KO Vehicle 24h
#> 17 dH1B KO Vehicle 0h
#> 18 dH1B KO Vehicle 12h
#> 19 dH1C KO <NA> <NA>
#> 20 dH1C <NA> Dex 0h
#> 21 dH1C <NA> Dex 12h
#> 22 dH1C <NA> Dex 24h
#> 23 dH1C <NA> Vehicle 0h
#> 24 dH1C <NA> Vehicle 12h
#> 25 dH1C <NA> Vehicle 24h
# but it can be resolved by merging df6 and df6b
mergeAllXY(df4, df4b, df5, mergeAllXY(df6, df6b))
#> CellLine Treatment Time Type
#> 1 dH1A Dex 0h KO
#> 2 dH1A Vehicle 0h KO
#> 3 dH1A Dex 12h KO
#> 4 dH1A Dex 24h KO
#> 5 dH1A Vehicle 12h KO
#> 6 dH1A Vehicle 24h KO
#> 7 dH1B Dex 0h KO
#> 8 dH1B Dex 12h KO
#> 9 dH1B Vehicle 0h KO
#> 10 dH1B Vehicle 12h KO
#> 11 dH1B Dex 24h KO
#> 12 dH1B Vehicle 24h KO
#> 13 dH1C Dex 0h KO
#> 14 dH1C Dex 12h KO
#> 15 dH1C Dex 24h KO
#> 16 dH1C Vehicle 0h KO
#> 17 dH1C Vehicle 12h KO
#> 18 dH1C Vehicle 24h KO
#> 19 ul3 Dex 0h Control
#> 20 ul3 Dex 12h Control
#> 21 ul3 Dex 24h Control
#> 22 ul3 Vehicle 0h Control
#> 23 ul3 Vehicle 12h Control
#> 24 ul3 Vehicle 24h Control
# it may be easier to recognize by sorting with mixedSortDF()
mixedSortDF(honorFactor=TRUE,
mergeAllXY(df4, df4b, df5, mergeAllXY(df6, df6b)))
#> CellLine Treatment Time Type
#> 22 ul3 Vehicle 0h Control
#> 23 ul3 Vehicle 12h Control
#> 24 ul3 Vehicle 24h Control
#> 19 ul3 Dex 0h Control
#> 20 ul3 Dex 12h Control
#> 21 ul3 Dex 24h Control
#> 2 dH1A Vehicle 0h KO
#> 5 dH1A Vehicle 12h KO
#> 6 dH1A Vehicle 24h KO
#> 1 dH1A Dex 0h KO
#> 3 dH1A Dex 12h KO
#> 4 dH1A Dex 24h KO
#> 9 dH1B Vehicle 0h KO
#> 10 dH1B Vehicle 12h KO
#> 12 dH1B Vehicle 24h KO
#> 7 dH1B Dex 0h KO
#> 8 dH1B Dex 12h KO
#> 11 dH1B Dex 24h KO
#> 16 dH1C Vehicle 0h KO
#> 17 dH1C Vehicle 12h KO
#> 18 dH1C Vehicle 24h KO
#> 13 dH1C Dex 0h KO
#> 14 dH1C Dex 12h KO
#> 15 dH1C Dex 24h KO
# again, factor order is maintained
mergeAllXY(df4, df4b, df5, sort=FALSE, mergeAllXY(df6, df6b))$CellLine
#> [1] ul3 ul3 ul3 ul3 ul3 ul3 dH1A dH1A dH1A dH1A dH1A dH1A dH1B dH1B dH1B
#> [16] dH1B dH1B dH1B dH1C dH1C dH1C dH1C dH1C dH1C
#> Levels: ul3 dH1A dH1B dH1C
# the result can be sorted properly
mixedSortDF(honorFactor=TRUE,
mergeAllXY(df4, df4b, df5, mergeAllXY(df6, df6b)))
#> CellLine Treatment Time Type
#> 22 ul3 Vehicle 0h Control
#> 23 ul3 Vehicle 12h Control
#> 24 ul3 Vehicle 24h Control
#> 19 ul3 Dex 0h Control
#> 20 ul3 Dex 12h Control
#> 21 ul3 Dex 24h Control
#> 2 dH1A Vehicle 0h KO
#> 5 dH1A Vehicle 12h KO
#> 6 dH1A Vehicle 24h KO
#> 1 dH1A Dex 0h KO
#> 3 dH1A Dex 12h KO
#> 4 dH1A Dex 24h KO
#> 9 dH1B Vehicle 0h KO
#> 10 dH1B Vehicle 12h KO
#> 12 dH1B Vehicle 24h KO
#> 7 dH1B Dex 0h KO
#> 8 dH1B Dex 12h KO
#> 11 dH1B Dex 24h KO
#> 16 dH1C Vehicle 0h KO
#> 17 dH1C Vehicle 12h KO
#> 18 dH1C Vehicle 24h KO
#> 13 dH1C Dex 0h KO
#> 14 dH1C Dex 12h KO
#> 15 dH1C Dex 24h KO