Refining Datensatz R-Studio mit

Question

SampleData.xlsx

Typ A1001 A1002 A1003 A1004 A1005 Gesamt TypeA
TypeB
TypC
typisiert
Gesamt

Ich habe die Daten in der obigen Form gesetzt verfeinern mit R-Programmierung. Suchen Sie nach einer Idee, um jede Art von Kommunikation zu zählen w.r.t UserID

 * 

data11 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData1", header = TRUE) 
data22 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData2", header = TRUE) 
dim(data11) 
dim(data22) 
data2 = data22[complete.cases(data22),] 
data2$User <- as.character(data2$User) 
data1$User = NA 
for(i in data1[,1]) 
{ 
    for(q in data2[,1]) 
    { 
     if(data1$Id[i] == data2$Id[q]) 
     { 
    data1$User[i] = data2$User[q] 
     } 
    } 
} 
data.1 = data1[complete.cases(data1),] 
x1 <- subset(data.1, Type == "Email") 
x2 <- subset(data.1, Type == "Update") 
x3 <- subset(data.1, Type == "NA") 
x4 <- subset(data.1, Type == "Call") 
x5 <- subset(data.1, Type == "Visit") 
p1 = as.list(as.data.frame(count(x1, "User"))) 
Type1 = p1$freq 

*

Wie Sie aus den letzten beiden Zeilen Code sehen. Ich habe etwas versucht, aber es ist der falsche Weg.

mir Hilfe

Answer 1

out Wenn Sie zuerst die fehlenden Codezeile korrigieren:

data1 = data11[complete.cases(data11),] 

Sie können dann verschmelzen und Lauftabelle. (Ich habe keine "count" Funktion in meinem R Arbeitsplatz.)

dmerge=merge(data1,data2, by=c("Id", "Id")) 
table(dmerge$Id, dmerge$Type) 
#----------------------- 
     Call Email NA Update Visit 
    10121 0  1 0  0  0 
    10122 0  1 0  0  0 
    1
    10124 0  1 0  0  0 
    10125 0  1 0  0  0 
    10126 0  1 0  0  0 
    10127 0  2 2  0  0 
    10129 0  0 0  1  0 
    10130 0  0 0  1  0 
    trimming the rest of a long table..... 

Answer 2

Dies ist ein R Markdown-Dokument.

library(xlsx) 

data11 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData1", header = TRUE) 
data22 <- read.xlsx("SampleData.xlsx", sheetName = "SampleData2", header = TRUE) 


    data2 = data22[complete.cases(data22),] 
    data1 = data11[complete.cases(data11),] 
    data1$User = NA 

    data2$User <- as.character(data2$User) 

    for(i in data1[,1]) 
{ 
    for(q in data2[,1]) 
    { 
     if(data1$Id[i] == data2$Id[q]) 
     { 
    data1$User[i] = data2$User[q] 
     } 
    } 
} 

data.1 = data1[complete.cases(data1),] 
summary(data1) 
``` 

```{r, echo=FALSE} 
x1 <- subset(data.1, Type == "Email") 
x2 <- subset(data.1, Type == "Update") 
x3 <- subset(data.1, Type == "NA") 
x4 <- subset(data.1, Type == "Call") 
x5 <- subset(data.1, Type == "Visit") 
``` 

```{r} 
newd <- table(data1$Type, data1$User) 
net = as.data.frame.matrix(newd) 
net$Total = net$A1001 + net$A1002 + net$A1003 + net$A1004 + net$A1005 

print(net) 

```