Zusammenführen mehrerer Datenrahmen auf zwei gemeinsamen Spalten
https://stackoverflow.com/questions/4199798
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Ich habe einige Fragen gesehen zu verschmelzen csv-Dateien in ein Datenrahmen. Was passiert, wenn die Datenrahmen bereits im Arbeitsbereich sind. Ich habe fünf breite Zoos, dass ich als Datenrahmen gegossen, dann schmelzen. Hier ist der Kopf eines:
> head(df.mon.ssf.ret)
date variable value
1 2009.000 AA1C NA
2 2009.083 AA1C NA
3 2009.167 AA1C NA
4 2009.250 AA1C NA
5 2009.333 AA1C NA
6 2009.417 AA1C NA
Ich konnte diese auf „Datum“ und „Variable“ mit einer Reihe von verschachtelten verschmilzt verschmelzen, aber das scheint ungeschickt. Gibt es eine programmatische Art und Weise zu verschmelzen?
Wenn ich zuversichtlich, dass die Spalten in derselben Reihenfolge in allen von den Zoos sind, kann ich sicher sein, dass Schmelze, dass eine Bestellung und Verwendung cbind hält? Dank!
Update:
Es gibt etwas, das ich über die Verwendung Philosophie der Schmelze bin fehlt. Hier ist, was passiert, wenn ich als Zoo verschmelzen und schmelzen als sehr breiten Datenrahmen drei der Zoos mit:
> temp <- merge(z.ssf.oi, z.ssf.oig, z.ssf.ret)
> class(temp)
[1] "zoo"
> temp2 <- cbind(index(temp), as.data.frame(temp))
> class(temp2)
[1] "data.frame"
> names(temp2)[1] <- "date"
> dim(temp2)
[1] 12 1204
> temp3 <- melt(temp2, id="date")
Error in data.frame(ids, variable, value) :
arguments imply differing number of rows: 12, 14436
> head(temp2)[, 1:5]
date AA1C.z.ssf.oi AAPL1C.z.ssf.oi ABT1C.z.ssf.oi ABX1C.z.ssf.oi
Jan 2009 Jan 2009 1895.800 49191.25 NA NA
Feb 2009 Feb 2009 1415.579 42650.26 NA 6267.96
Mar 2009 Mar 2009 1501.398 36712.20 NA 11581.65
Apr 2009 Apr 2009 1752.936 74376.27 NA 12168.29
May 2009 May 2009 1942.874 96307.30 NA 13490.60
Jun 2009 Jun 2009 NA 79170.70 NA 16337.21
Update 2: Vielen Dank für die Hilfe! Hier ist eine sehr manuelle Lösung
> A <- cbind(index(z.ssf.oi), as.data.frame(z.ssf.oi))
> names(A)[1] <- "date"
> B <- cbind(index(z.ssf.oig), as.data.frame(z.ssf.oig))
> names(B)[1] <- "date"
> C <- cbind(index(z.ssf.ret), as.data.frame(z.ssf.ret))
> names(C)[1] <- "date"
> A.melt <- melt(A, id="date")
> head(A.melt)
date variable value
1 Jan 2009 A1C NA
2 Feb 2009 A1C NA
3 Mar 2009 A1C NA
4 Apr 2009 A1C NA
5 May 2009 A1C NA
6 Jun 2009 A1C NA
> B.melt <- melt(B, id="date")
> C.melt <- melt(C, id="date")
> ans <- merge(merge(A.melt, B.melt, by=c("date", "variable")), C.melt, by=c("date", "variable"))
> names(ans)[3:5] <- c("oi", "oig", "ret")
> head(ans)
date variable oi oig ret
1 Apr 2009 A1C NA NA NA
2 Apr 2009 AA1C NA NA NA
3 Apr 2009 AAPL1C 59316.88 0.3375786 0.008600073
4 Apr 2009 ABB1C NA NA NA
5 Apr 2009 ABT1C NA NA NA
6 Apr 2009 ABX1C NA NA NA
(und die nationalen Agenturen sind von einem unvollständigen Datensatz zu Hause und mit dem Rad in der Filterung aus meiner Datenbank benötigt)
Update 3: Hier sind einige dputs (Ich nahm die [01.10, 01.10] Teilmengen jeden breiten Zoos und konvertierte zum Datenrahmen)
> dput(A)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), class = "factor", .Label = "oi"), date = structure(c(2009,
2009.08333333333, 2009.16666666667, 2009.25, 2009.33333333333,
2009.41666666667, 2009.5, 2009.58333333333, 2009.66666666667,
2009.75), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(49226.391, 42662.1589473684, 35354.4254545455,
57161.6495238095, 84362.895, NA, NA, 47011.8519047619, 57852.2171428571,
33058.0090909091), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_),
ABX1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACE1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_), ACI1C = c(NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), ACS1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_)), .Names = c("group", "date",
"AA1C", "AAPL1C", "ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C",
"ADBE1C", "ADCT1C", "ADI1C"), row.names = c("Jan 2009", "Feb 2009",
"Mar 2009", "Apr 2009", "May 2009", "Jun 2009", "Jul 2009", "Aug 2009",
"Sep 2009", "Oct 2009"), class = "data.frame")
> dput(B)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), class = "factor", .Label = "oig"), date = structure(c(2009.08333333333,
2009.16666666667, 2009.25, 2009.33333333333, 2009.41666666667,
2009.5, 2009.58333333333, 2009.66666666667, 2009.75, 2009.83333333333
), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(-0.143117562125788, -0.187888745830302, 0.480459636485712,
0.389244461579155, NA, NA, NA, 0.207492040517069, -0.559627909130612,
NA), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ABX1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), ACE1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ACI1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACS1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_)), .Names = c("group", "date", "AA1C", "AAPL1C",
"ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C", "ADBE1C", "ADCT1C",
"ADI1C"), row.names = c("Feb 2009", "Mar 2009", "Apr 2009", "May 2009",
"Jun 2009", "Jul 2009", "Aug 2009", "Sep 2009", "Oct 2009", "Nov 2009"
), class = "data.frame")
> dput(C)
structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), class = "factor", .Label = "ret"), date = structure(c(2009,
2009.08333333333, 2009.16666666667, 2009.25, 2009.33333333333,
2009.41666666667, 2009.5, 2009.58333333333, 2009.66666666667,
2009.75), class = "yearmon"), AA1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), AAPL1C = c(-0.143117562125788, -0.187888745830302, 0.480459636485712,
0.389244461579155, NA, NA, NA, 0.207492040517069, -0.559627909130612,
NA), ABT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ABX1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), ACE1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ACI1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ACS1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), ADBE1C = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
), ADCT1C = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), ADI1C = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_)), .Names = c("group", "date", "AA1C", "AAPL1C",
"ABT1C", "ABX1C", "ACE1C", "ACI1C", "ACS1C", "ADBE1C", "ADCT1C",
"ADI1C"), row.names = c("Feb 2009", "Mar 2009", "Apr 2009", "May 2009",
"Jun 2009", "Jul 2009", "Aug 2009", "Sep 2009", "Oct 2009", "Nov 2009"
), class = "data.frame")
Lösung
Sie können dies versuchen. Ungeprüfte da Ihr Beispiel ist nicht reproduzierbar. Geben Sie uns einige Dummy-Daten für z.sfff.oi, z.sff.oig und z.sff.ret, wenn Sie eine bessere Antwort wollen. Sie können dput () verwenden, um Code für eine reproduzierbare Datenmenge zu erzeugen.
A <- data.frame(Group = "oi", date = as.factor(index(z.ssf.oi),) as.data.frame(z.ssf.oi)))
B <- data.frame(Group = "oig", date = as.factor(index(z.ssf.oig)), as.data.frame(z.ssf.oig)))
C <- data.frame(Group = "ret", date = as.factor(index(z.ssf.ret)), as.data.frame(z.ssf.ret)))
Long <- melt(rbind(A, B, C), id.vars = c("Group", "date")))
cast(date ~ Group, data = Long)
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