Introduction: This is project 1

Set up working directory

setwd("C:/Users/blake/OneDrive/R MKTG")

# Load datasets
Car1 <- read.csv("Car_Survey_1.csv")
str(Car1)
## 'data.frame':    1180 obs. of  23 variables:
##  $ Resp        : chr  "Res1" "Res2" "Res3" "Res4" ...
##  $ Att_1       : int  6 7 7 4 6 6 1 6 3 6 ...
##  $ Att_2       : int  6 5 7 1 6 6 1 5 2 6 ...
##  $ Enj_1       : int  6 5 7 1 6 6 1 5 3 4 ...
##  $ Enj_2       : int  6 2 5 1 5 5 1 3 2 4 ...
##  $ Perform_1   : int  5 2 5 1 5 5 2 5 2 4 ...
##  $ Perform_2   : int  6 6 5 1 2 5 2 5 3 4 ...
##  $ Perform_3   : int  3 7 3 1 1 7 2 2 1 1 ...
##  $ WOM_1       : int  3 5 6 7 7 5 2 4 6 5 ...
##  $ WOM_2       : int  3 5 6 7 7 5 3 6 6 6 ...
##  $ Futu_Pur_1  : int  3 6 7 3 7 7 5 4 7 6 ...
##  $ Futu_Pur_2  : int  3 6 7 3 6 7 2 4 7 6 ...
##  $ Valu_Percp_1: int  5 6 5 6 6 7 2 4 6 6 ...
##  $ Valu_Percp_2: int  2 7 7 5 5 7 2 4 6 6 ...
##  $ Pur_Proces_1: int  6 7 7 5 6 7 2 4 6 6 ...
##  $ Pur_Proces_2: int  4 6 7 4 7 7 6 4 6 6 ...
##  $ Residence   : int  2 2 1 2 1 2 2 1 2 1 ...
##  $ Pay_Meth    : int  2 2 2 2 2 2 2 2 2 2 ...
##  $ Insur_Type  : chr  "Collision" "Collision" "Collision" "Collision" ...
##  $ Gender      : chr  "Male" "Male" "Male" "Male" ...
##  $ Age         : int  18 18 19 19 19 19 19 21 21 21 ...
##  $ Education   : int  2 2 2 2 2 2 2 2 2 2 ...
##  $ X           : logi  NA NA NA NA NA NA ...
head(Car1, n=5)
##   Resp Att_1 Att_2 Enj_1 Enj_2 Perform_1 Perform_2 Perform_3 WOM_1 WOM_2
## 1 Res1     6     6     6     6         5         6         3     3     3
## 2 Res2     7     5     5     2         2         6         7     5     5
## 3 Res3     7     7     7     5         5         5         3     6     6
## 4 Res4     4     1     1     1         1         1         1     7     7
## 5 Res5     6     6     6     5         5         2         1     7     7
##   Futu_Pur_1 Futu_Pur_2 Valu_Percp_1 Valu_Percp_2 Pur_Proces_1 Pur_Proces_2
## 1          3          3            5            2            6            4
## 2          6          6            6            7            7            6
## 3          7          7            5            7            7            7
## 4          3          3            6            5            5            4
## 5          7          6            6            5            6            7
##   Residence Pay_Meth Insur_Type Gender Age Education  X
## 1         2        2  Collision   Male  18         2 NA
## 2         2        2  Collision   Male  18         2 NA
## 3         1        2  Collision   Male  19         2 NA
## 4         2        2  Collision   Male  19         2 NA
## 5         1        2  Collision Female  19         2 NA
View(Car1)

Car2 <- read.csv("Car_Survey_2.csv")
str(Car2)
## 'data.frame':    1049 obs. of  9 variables:
##  $ Respondents: chr  "Res1" "Res2" "Res3" "Res4" ...
##  $ Region     : chr  "European" "European" "European" "European" ...
##  $ Model      : chr  "Ford Expedition" "Ford Expedition" "Ford Expedition" "Ford Expedition" ...
##  $ MPG        : int  15 15 15 15 15 15 15 15 15 15 ...
##  $ Cyl        : int  8 8 8 8 8 8 8 8 8 8 ...
##  $ acc1       : num  5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 ...
##  $ C_cost.    : num  16 16 16 16 16 16 16 16 16 16 ...
##  $ H_Cost     : num  14 14 14 14 14 14 14 14 14 14 ...
##  $ Post.Satis : int  4 3 5 5 5 3 3 6 3 5 ...
head(Car2, n=5)
##   Respondents   Region           Model MPG Cyl acc1 C_cost. H_Cost Post.Satis
## 1        Res1 European Ford Expedition  15   8  5.5      16     14          4
## 2        Res2 European Ford Expedition  15   8  5.5      16     14          3
## 3        Res3 European Ford Expedition  15   8  5.5      16     14          5
## 4        Res4 European Ford Expedition  15   8  5.5      16     14          5
## 5        Res5 European Ford Expedition  15   8  5.5      16     14          5
View(Car2)

# Rename first column of Car2
names(Car2)[1] <- "Resp"
head(Car2, n=1)
##   Resp   Region           Model MPG Cyl acc1 C_cost. H_Cost Post.Satis
## 1 Res1 European Ford Expedition  15   8  5.5      16     14          4
# Merge data frames by "Resp" column
Car_Total <- merge(Car1, Car2, by="Resp")
str(Car_Total)
## 'data.frame':    1049 obs. of  31 variables:
##  $ Resp        : chr  "Res1" "Res10" "Res100" "Res1000" ...
##  $ Att_1       : int  6 6 6 6 6 3 2 7 2 6 ...
##  $ Att_2       : int  6 6 7 6 6 1 2 7 1 6 ...
##  $ Enj_1       : int  6 4 7 7 7 4 1 7 2 6 ...
##  $ Enj_2       : int  6 4 3 6 6 3 2 6 1 5 ...
##  $ Perform_1   : int  5 4 5 6 6 5 2 5 2 5 ...
##  $ Perform_2   : int  6 4 6 6 6 6 2 6 2 5 ...
##  $ Perform_3   : int  3 1 6 6 6 6 1 5 2 5 ...
##  $ WOM_1       : int  3 5 3 6 4 2 6 6 7 3 ...
##  $ WOM_2       : int  3 6 5 6 4 6 7 6 7 3 ...
##  $ Futu_Pur_1  : int  3 6 6 6 4 6 6 6 7 6 ...
##  $ Futu_Pur_2  : int  3 6 6 6 6 6 5 7 7 6 ...
##  $ Valu_Percp_1: int  5 6 7 4 5 5 4 6 4 5 ...
##  $ Valu_Percp_2: int  2 6 6 6 6 4 4 5 6 6 ...
##  $ Pur_Proces_1: int  6 6 5 6 6 5 4 5 6 6 ...
##  $ Pur_Proces_2: int  4 6 5 3 7 5 5 5 7 5 ...
##  $ Residence   : int  2 1 2 2 1 1 1 2 1 2 ...
##  $ Pay_Meth    : int  2 2 1 3 3 3 3 3 3 3 ...
##  $ Insur_Type  : chr  "Collision" "Collision" "Collision" "Liability" ...
##  $ Gender      : chr  "Male" "Male" "Female" "Female" ...
##  $ Age         : int  18 21 32 24 24 25 26 26 27 27 ...
##  $ Education   : int  2 2 1 2 2 2 2 2 2 2 ...
##  $ X           : logi  NA NA NA NA NA NA ...
##  $ Region      : chr  "European" "European" "American" "Asian" ...
##  $ Model       : chr  "Ford Expedition" "Ford Expedition" "Toyota Rav4" "Toyota Corolla" ...
##  $ MPG         : int  15 15 24 26 26 26 26 26 26 26 ...
##  $ Cyl         : int  8 8 4 4 4 4 4 4 4 4 ...
##  $ acc1        : num  5.5 5.5 8.2 8 8 8 8 8 8 8 ...
##  $ C_cost.     : num  16 16 10 7 7 7 7 7 7 7 ...
##  $ H_Cost      : num  14 14 8 6 6 6 6 6 6 6 ...
##  $ Post.Satis  : int  4 5 4 6 5 6 5 6 7 6 ...
# Save the merged data frame to a CSV file
write.csv(Car_Total, "Car_Total.csv", row.names=FALSE) # Avoid row numbers
View(Car_Total)