Umwandlung long in wide format / Zusammenfügen von Zeilen

[alina222]

Hallo,

ich möchte meinen Datensatz aufbereiten und bin dabei auf folgendes Problem gestoßen:

Die Probanden haben zu verschiedenen Zeiten randomisiert Teile eines Fragebogens beantwortet was zu einem Datensatz in Form wie folgendes Beispiel geführt hat (wie ein long format mit verschiedenen Zeitpunkten und somit mehreren Zeilen für eine Person, jedoch insgesamt pro Person nur ein kompletter Fragebogen, da immer nur Teile beantwortet wurden):
Die Punkte sollen nur verdeutlichen dass es pro Fragebogenteil mehr als nur zwei Fragen waren.

VP, SA1, SA2, .... PD1, PD2, .... PK1, PK2, ....
1 , NA, NA, ... 2, 1, ... NA, NA
1, 1, 1 , ... NA, NA, ... NA, NA
1, NA, NA , ... NA, NA, ... 2 , 1
2, 1 , 2 , ... NA, NA, ... NA, NA
2, NA, NA , ... NA, NA, ... 1 , 1
2, NA , NA , ... 2, 1, ... NA , NA
.
.

Nun brauche ich für meine Auswertungen aber ein Format, indem pro Person nur eine Zeile vorliegt, jedoch die Informationen aus allen Zeilen einer Person kombiniert werden, die Zeile also erstellt wird indem die Missings durch die Daten in den anderen Zeilen einer Person ersetzt werden.

Das ganze sollte also im Endeffekt so aussehen:

VP, SA1, SA2, ... PD1, PD2, .... PK1, PK2, ...
1 , 1 , 1 , ... 2 , 1, ... 2, 1
2 , 1 , 2 , ... 2 , 1, ... 1, 1
.
.
.

Ich habe an den reshape oder den cast Befehl gedacht, so wie ich es verstanden habe (bzw. hat die Google Suche so erklärt) funktioniert das nur wenn man eine Spalte hat, die den Zeitpunkt oder "Values" enthält, welche dann zu den neuen Variablen im wide Format werden. Das habe ich ja aber nicht sondern in den Zeilen sollen die selben Variablen stehen, nur der Inhalt aus mehreren soll übernommen werden.

Vielen Dank schonmal für eure Hilfe!
Alina

[student]

Hallo Alina,

willkommen im Forum. Zum long und wide-Format habe ich hier mal etwas gemacht. Vielleicht hilft es weiter...

[bigben]

Geht das in die gewünschte Richtung?

Code: Alles auswählen

bsp <- read.csv(header=TRUE, text="VP, SA1, SA2, PD1, PD2, PK1, PK2
1,NA,NA,2,1,NA,NA
1,1,1,NA,NA,NA,NA
1,NA,NA,NA,NA,2,1
2,1,2,NA,NA,NA,NA
2,NA,NA,NA,NA,1,1
2,NA,NA,2,1,NA,NA")


erg <- tapply(X=bsp[,2:7], 
              INDEX = list(bsp$VP), 
              FUN = function(x) colMeans(x, na.rm = TRUE))
print(erg)

LG,
Bernhard

[EDi]

Oder eine dplyr-Lösung:

Code: Alles auswählen

bsp <- read.csv(header=TRUE, text="VP, SA1, SA2, PD1, PD2, PK1, PK2
1,NA,NA,2,1,NA,NA
1,1,1,NA,NA,NA,NA
1,NA,NA,NA,NA,2,1
2,1,2,NA,NA,NA,NA
2,NA,NA,NA,NA,1,1
2,NA,NA,2,1,NA,NA")

library(dplyr)
bsp %>%
  group_by(VP) %>%
  summarise_all(function(x) x[!is.na(x)])
  # or as lambda function
  # summarise_all(~ .x[!is.na(.x)])
  

[alina222]

Vielen Dank schonmal für die schnelle Hilfe!!!

Bei der dplyr Lösung kommt folgende Fehlermeldung:

> df %>%
+ group_by(session) %>%
+ summarise_all(function(x) x[!is.na(x)])
Error in function_list[[k]](value) :
could not find function "summarise_all"
> # or as lambda function
> # summarise_all(~ .x[!is.na(.x)])
> df %>%
+ group_by(session) %>%
+ summarize_all(function(x) x[!is.na(x)])
Error in function_list[[k]](value) :
could not find function "summarize_all"

Ich habe es mit summarise_all und summarize_all probiert...
Könnte es an folgender Warnung liegen, welche beim Laden des dplyr Paketes kommt?
Attache Paket: ‘dplyr’

The following objects are masked from ‘package:stats’:

filter, lag

The following objects are masked from ‘package:base’:

intersect, setdiff, setequal, union

Warning message:
Paket ‘dplyr’ wurde unter R Version 3.1.3 erstellt

Ich habe das Paket bereits nochmal aktualisiert/neu heruntergeladen, das hat aber leider nichts gebracht.



Bei der anderen Lösung mit dem tapply Befehl kommt folgende Fehlermeldung:

> erg <- tapply(X=df.red2[,2:74],
+ INDEX = list(df.red2$session),
+ FUN = function(x) colMeans(x, na.rm = TRUE))
Error in tapply(X = df.red2[, 2:74], INDEX = list(df.red2$session), FUN = function(x) colMeans(x, :
Argumente müssen die selbe Länge haben

Ich habe bereits einen reduzierten Datensatz erstellt, welcher nur die Variablen enthält welche ersetzt werden müssen.
Könnte es daran liegen, dass nicht von jedem Probanden die Antworten auf alle Fragen vorliegen, sondern Probanden auch abgebrochen haben und von einzelnen dann z.B nur die Antworten auf die SA Fragen vorliegen? Wenn ja gäbe es dafür eine Lösung?

Vielen Dank nocheinmal für die Hilfe!

[bigben]

Hallo alina,

sei so nett, und gib uns einen Einblick in Deine Originaldaten. Beispielsweise könntest du uns den Output folgender Zeile in code-Tags hier ins Forum posten:

Code: Alles auswählen

dput(head(df.red2, 20))

Natürlich nicht, wenn da Klarnamen, Telefonnummern oder Emailadressen drin stehen.

LG,
Bernhard

[alina222]

Hallo Bernhard,

ich weiß nicht was ein Code Tag ist, aber hier ist der Output von dem Befehl:

Code: Alles auswählen

dput(head(df.red2, 20))
structure(list(session = structure(c(1L, 136L, 136L, 136L, 136L, 
136L, 136L, 59L, 28L, 135L, 52L, 52L, 52L, 52L, 52L, 52L, 36L, 
36L, 36L, 36L), .Label = c("", "-GK5NM8WY-5hlWsTj1Q4yY_VHsZW7JOljK3Zk2STl9wQ88MIo86_yKOBuQxRPmm9", 
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"zealousOstrichXXXGsD82k867IR378xg__gb1i2nrx_qoqcjLKmy9E3teom8ZZo", 
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"ZwRSa_ApOgHBzMNIo10HU-xGCIxuL0uXbBD2tmCQZiaZ75KcJVCxrb2jE3wPlXG6"
), class = "factor"), SA_koerperlich = c(2L, NA, 2L, NA, NA, 
NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), 
    SA_Behinderung = c(2L, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Verdacht_Behinderung = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Inzest = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Minderjaehrig = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_spaet = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Vergewaltigung = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Frist = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Wunsch = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Verboten = c(2L, NA, 2L, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), 
    SA_Kosten = c(2L, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Eltern_straffrei = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Arzt_straffrei = c(2L, NA, 2L, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L
    ), PND_Verdacht = c(2L, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Erbkrankheit = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_RS = c(2L, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Geschlecht = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Erbkrankheit_Erw = c(2L, NA, NA, NA, 
    NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA), PND_Standard = c(2L, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Verbot = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Kosten = c(2L, NA, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Eltern_straffei = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Arzt_straffei = c(2L, NA, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA
    ), PID_Alter = c(2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Erbkrankheit = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_kuenstlich = c(2L, NA, NA, NA, NA, NA, 
    2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), 
    PID_Genetik_Erkrankung = c(2L, NA, NA, NA, NA, NA, 2L, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Geschlecht = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Erbgut = c(2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Organspendung = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_erlaubt = c(2L, NA, NA, NA, NA, NA, 
    2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), 
    PID_verboten = c(2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Kosten = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Land = c(2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Eltern_straffrei = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Arzt_straffrei = c(2L, NA, NA, NA, NA, 
    NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA
    ), PKD_Vorgeschichte = c(2L, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Erbkrankheit = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_jeder = c(2L, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_schwere_Erkrankung = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_behandelbareK = c(2L, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA
    ), PKD_Krankheiten = c(2L, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Krankheiten_Erw = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_koerperliche_Besonderheiten = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_alles_erlaubt = c(2L, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA
    ), PKD_verboten = c(2L, 2L, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Kosten = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_Eltern_straffrei = c(2L, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA), PKD_Arzt_straffrei = c(2L, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), Crisp_schwere_Krankheit = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_behandelbare_Krankheit = c(2L, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, 
    NA, NA, NA), Crisp_Krankheiten_Erw = c(2L, NA, NA, NA, 2L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA
    ), Crisp_Merkmale_auserlich = c(2L, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_Merkmale_PE = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_Design = c(2L, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), 
    Crisp_Wunsch = c(2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_verboten = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_Kosten = c(2L, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), 
    Crisp_Eltern_straffrei = c(2L, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_Arzt_straffrei = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), KB_Frauen_keine_Kinder = c(2L, NA, NA, 2L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA), KB_Eizellspende = c(2L, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Spermaspende = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_Embryonenspende = c(2L, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA
    ), KB_Verstorbene = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Alleinstehende = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_ueber_40 = c(2L, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), 
    KB_Homosexuell = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_wunsch_Eltern = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_verboten = c(2L, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), 
    KB_Kosten = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Paare_straffrei = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_Arzt_straffrei = c(2L, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA
    )), .Names = c("session", "SA_koerperlich", "SA_Behinderung", 
"SA_Verdacht_Behinderung", "SA_Inzest", "SA_Minderjaehrig", "SA_spaet", 
"SA_Vergewaltigung", "SA_Frist", "SA_Wunsch", "SA_Verboten", 
"SA_Kosten", "SA_Eltern_straffrei", "SA_Arzt_straffrei", "PND_Verdacht", 
"PND_Erbkrankheit", "PND_RS", "PND_Geschlecht", "PND_Erbkrankheit_Erw", 
"PND_Standard", "PND_Verbot", "PND_Kosten", "PND_Eltern_straffei", 
"PND_Arzt_straffei", "PID_Alter", "PID_Erbkrankheit", "PID_kuenstlich", 
"PID_Genetik_Erkrankung", "PID_Geschlecht", "PID_Erbgut", "PID_Organspendung", 
"PID_erlaubt", "PID_verboten", "PID_Kosten", "PID_Land", "PID_Eltern_straffrei", 
"PID_Arzt_straffrei", "PKD_Vorgeschichte", "PKD_Erbkrankheit", 
"PKD_jeder", "PKD_schwere_Erkrankung", "PKD_behandelbareK", "PKD_Krankheiten", 
"PKD_Krankheiten_Erw", "PKD_koerperliche_Besonderheiten", "PKD_alles_erlaubt", 
"PKD_verboten", "PKD_Kosten", "PKD_Eltern_straffrei", "PKD_Arzt_straffrei", 
"Crisp_schwere_Krankheit", "Crisp_behandelbare_Krankheit", "Crisp_Krankheiten_Erw", 
"Crisp_Merkmale_auserlich", "Crisp_Merkmale_PE", "Crisp_Design", 
"Crisp_Wunsch", "Crisp_verboten", "Crisp_Kosten", "Crisp_Eltern_straffrei", 
"Crisp_Arzt_straffrei", "KB_Frauen_keine_Kinder", "KB_Eizellspende", 
"KB_Spermaspende", "KB_Embryonenspende", "KB_Verstorbene", "KB_Alleinstehende", 
"KB_ueber_40", "KB_Homosexuell", "KB_wunsch_Eltern", "KB_verboten", 
"KB_Kosten", "KB_Paare_straffrei", "KB_Arzt_straffrei"), row.names = c(NA, 
20L), class = "data.frame")

Die langen Zahlen/Buchstaben Kombinationen sind die, vom Programm mit dem ich die Umfrage gemacht habe erstellten, Session Codes mit welchen die Zuordnung zur Versuchsperson möglich ist (also gleicher Session code heißt gleiche Versuchsperson)

bigben hat code-Tags ergänzt, siehe auch viewtopic.php?f=20&t=29

[bigben]

Setzen wir Deine Daten als "bsp":

Code: Alles auswählen

bsp <- structure(list(session = structure(c(1L, 136L, 136L, 136L, 136L, 
136L, 136L, 59L, 28L, 135L, 52L, 52L, 52L, 52L, 52L, 52L, 36L, 
36L, 36L, 36L), .Label = c("", "-GK5NM8WY-5hlWsTj1Q4yY_VHsZW7JOljK3Zk2STl9wQ88MIo86_yKOBuQxRPmm9", 
"_z2aDQUDZi1orGJNlugMoGqXoXpdrp5ZrvzZ8p1Lu_vcFeCo4_qJA1TwYlldCRKD", 
"0Q60yev1O28YS2IWA9G72d99jBlk9Fi8h50HjEZA7St3snZwzt-mLzV_njQQpEH0", 
"2fGnOInmIf0HKAeHad_FGXuLkydNj4MJdQifCpbOTrJb5hk8ivd4382OJ19FheWZ", 
"4_Muulivqk-FFasifTjmTOaLhgIhfwNsR_GFM-AjdHy2Ucf1Dlk0lf5I5iQ75iVG", 
"46Yr1DWyi3BrmAXlTSae_5qYTHm_epBbTMARE_034mRk2pJ2lJ2uM13S7J0zHNwl", 
"46ZYH7Oh001-FoeDv6kMPYjNramE5QRohP8vPNyTT1rRa0coGAcvbN1uk3aAwYbs", 
"4Mf3rya4G0BbY4FBt66krtmcoozFw8qIsS2q5Is4HScDh8ULKGg-DxVJ4Je8AWVm", 
"4NBQZSImRgG9S25O2c6khge6ZZnPvGkOVmzVSSsSoQes4AfGSfgcxhnC3f0d9LO4", 
"4QBjhoDW9u5GFMCqTDdoZ7Xdg0M-O46Khx9BRN966qLGZxZI7TfIQ_JYjdUKiP-1", 
"5Lnl7G1KrcZct8Nm__XOG6ABpklpQt7O2yThtT19es-yeph4BpA2l1Gh02tWPDog", 
"5M-CJBHE_RyL8bhXgCzaeP7MwDfYCplsm8lNQXTLHKZFGYxHklcNhjCRAGbhSuhQ", 
"63F8feGuZPhMzkEUCKUrnENoRzf6yBKo-gQEBD7_HONRmylwctWQp0Ah4exIfOV1", 
"79uQqXUeupMezqJL7v0cen4CCrvj739teADCag17DcPboG1pchNd8zOxYXNQVQXA", 
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    SA_Behinderung = c(2L, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Verdacht_Behinderung = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Inzest = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Minderjaehrig = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_spaet = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Vergewaltigung = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Frist = c(2L, NA, 2L, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Wunsch = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Verboten = c(2L, NA, 2L, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L), 
    SA_Kosten = c(2L, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, 2L), SA_Eltern_straffrei = c(2L, 
    NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L), SA_Arzt_straffrei = c(2L, NA, 2L, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L
    ), PND_Verdacht = c(2L, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Erbkrankheit = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_RS = c(2L, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Geschlecht = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Erbkrankheit_Erw = c(2L, NA, NA, NA, 
    NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA), PND_Standard = c(2L, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Verbot = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Kosten = c(2L, NA, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA), PND_Eltern_straffei = c(2L, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA), PND_Arzt_straffei = c(2L, NA, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA
    ), PID_Alter = c(2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Erbkrankheit = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_kuenstlich = c(2L, NA, NA, NA, NA, NA, 
    2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), 
    PID_Genetik_Erkrankung = c(2L, NA, NA, NA, NA, NA, 2L, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Geschlecht = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Erbgut = c(2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Organspendung = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_erlaubt = c(2L, NA, NA, NA, NA, NA, 
    2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), 
    PID_verboten = c(2L, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Kosten = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Land = c(2L, NA, NA, NA, NA, NA, 2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA), PID_Eltern_straffrei = c(2L, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, 2L, NA, NA), PID_Arzt_straffrei = c(2L, NA, NA, NA, NA, 
    NA, 2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 2L, NA, NA
    ), PKD_Vorgeschichte = c(2L, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Erbkrankheit = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_jeder = c(2L, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_schwere_Erkrankung = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_behandelbareK = c(2L, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA
    ), PKD_Krankheiten = c(2L, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Krankheiten_Erw = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_koerperliche_Besonderheiten = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_alles_erlaubt = c(2L, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA
    ), PKD_verboten = c(2L, 2L, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), PKD_Kosten = c(2L, 
    2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, 2L, NA), PKD_Eltern_straffrei = c(2L, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, 
    NA), PKD_Arzt_straffrei = c(2L, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 2L, NA), Crisp_schwere_Krankheit = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_behandelbare_Krankheit = c(2L, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, 
    NA, NA, NA), Crisp_Krankheiten_Erw = c(2L, NA, NA, NA, 2L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA
    ), Crisp_Merkmale_auserlich = c(2L, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_Merkmale_PE = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_Design = c(2L, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), 
    Crisp_Wunsch = c(2L, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_verboten = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), Crisp_Kosten = c(2L, NA, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), 
    Crisp_Eltern_straffrei = c(2L, NA, NA, NA, 2L, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, 2L, NA, 2L, NA, NA, NA), Crisp_Arzt_straffrei = c(2L, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
    2L, NA, NA, NA), KB_Frauen_keine_Kinder = c(2L, NA, NA, 2L, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA), KB_Eizellspende = c(2L, NA, NA, 2L, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Spermaspende = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_Embryonenspende = c(2L, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA
    ), KB_Verstorbene = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Alleinstehende = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_ueber_40 = c(2L, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), 
    KB_Homosexuell = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_wunsch_Eltern = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_verboten = c(2L, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA), 
    KB_Kosten = c(2L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA), KB_Paare_straffrei = c(2L, 
    NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, 
    NA, NA, NA, NA), KB_Arzt_straffrei = c(2L, NA, NA, 2L, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA
    )), .Names = c("session", "SA_koerperlich", "SA_Behinderung", 
"SA_Verdacht_Behinderung", "SA_Inzest", "SA_Minderjaehrig", "SA_spaet", 
"SA_Vergewaltigung", "SA_Frist", "SA_Wunsch", "SA_Verboten", 
"SA_Kosten", "SA_Eltern_straffrei", "SA_Arzt_straffrei", "PND_Verdacht", 
"PND_Erbkrankheit", "PND_RS", "PND_Geschlecht", "PND_Erbkrankheit_Erw", 
"PND_Standard", "PND_Verbot", "PND_Kosten", "PND_Eltern_straffei", 
"PND_Arzt_straffei", "PID_Alter", "PID_Erbkrankheit", "PID_kuenstlich", 
"PID_Genetik_Erkrankung", "PID_Geschlecht", "PID_Erbgut", "PID_Organspendung", 
"PID_erlaubt", "PID_verboten", "PID_Kosten", "PID_Land", "PID_Eltern_straffrei", 
"PID_Arzt_straffrei", "PKD_Vorgeschichte", "PKD_Erbkrankheit", 
"PKD_jeder", "PKD_schwere_Erkrankung", "PKD_behandelbareK", "PKD_Krankheiten", 
"PKD_Krankheiten_Erw", "PKD_koerperliche_Besonderheiten", "PKD_alles_erlaubt", 
"PKD_verboten", "PKD_Kosten", "PKD_Eltern_straffrei", "PKD_Arzt_straffrei", 
"Crisp_schwere_Krankheit", "Crisp_behandelbare_Krankheit", "Crisp_Krankheiten_Erw", 
"Crisp_Merkmale_auserlich", "Crisp_Merkmale_PE", "Crisp_Design", 
"Crisp_Wunsch", "Crisp_verboten", "Crisp_Kosten", "Crisp_Eltern_straffrei", 
"Crisp_Arzt_straffrei", "KB_Frauen_keine_Kinder", "KB_Eizellspende", 
"KB_Spermaspende", "KB_Embryonenspende", "KB_Verstorbene", "KB_Alleinstehende", 
"KB_ueber_40", "KB_Homosexuell", "KB_wunsch_Eltern", "KB_verboten", 
"KB_Kosten", "KB_Paare_straffrei", "KB_Arzt_straffrei"), row.names = c(NA, 
20L), class = "data.frame")

Dann funktioniert bei mir folgendes:

Code: Alles auswählen

erg <- aggregate(x= bsp[,2:74], by=list(bsp$session), 
          FUN= function(x) mean(x, na.rm = TRUE))
print(erg)

Ist ein bisschen unübersichtlich: Es gibt eine session mit leerem Namen und überall dort, wo nur NA angegeben waren steht jetzt NaN (breakableCucscus ist ein Beispiel dafür). Andere Werte als "2" und "NA" scheinen in Deinen Daten nicht vorzukommen.

LG,
Bernhard

[alina222]

Hallo Bernhard,

vielen lieben Dank für deine Hilfe!!!

Es hat jetzt funktioniert indem ich die drei Zeilen ohne Session code noch aus dem Datensatz entfernt habe - vielen Dank!!


Genau, ich habe im Datensatz nur dichotome Items, also 1 und 2 für "ja" und "nein" und die NAs.
Bei mir hat es im reduzierten Datensatz korrekt die "NA" angezeigt und kein "NaN".
Nachdem ich den Datensatz aber mit deinem Befehl zusammengefügt habe erschienen fehlende Werte als "NaN".
Das werde ich jetzt einfach manuell mit folgendem Befehl beheben.

Code: Alles auswählen

is.na(erg$SA_Behinderung) <- which(erg$SA_Behinderung=="NaN")

Vielen Dank für die gute und super schnelle Hilfe (das ist für mich als Psychologiestudentin, die nur begrenzt R an der Uni lernt, wirklich Gold wert)!!
Liebe Grüße
Alina

[EDi]

Code: Alles auswählen

Warning message:
Paket ‘dplyr’ wurde unter R Version 3.1.3 erstellt 

Wie kann denn das sein, wenn das aktuelle dplyr R (≥ 3.2.0) verlangt? https://cran.r-project.org/web/packages ... index.html

Was sagt

Code: Alles auswählen

packageVersion('dplyr')