# 1. Import data ----------------------------------------------------------
library(readxl)
Sales <- read_xlsx("Line_Graphs.xlsx", sheet = "Sales")
Sales
## # A tibble: 13 x 3
## Period Product_A_Sold Product_B_Sold
## <dbl> <dbl> <dbl>
## 1 1 50 62
## 2 2 53 66
## 3 3 57 72
## 4 4 59 75
## 5 5 65 79
## 6 6 67 83
## 7 7 72 88
## 8 8 76 92
## 9 9 79 96
## 10 10 83 98
## 11 11 86 102
## 12 12 93 106
## 13 13 96 109
colnames(Sales)[2] <- "Product_A"
colnames(Sales)[3] <- "Product_B"
# 2. Melt data for plotting -----------------------------------------------
library(reshape2)
names(Sales)
## [1] "Period" "Product_A" "Product_B"
Sales_Long <- melt(Sales, id.vars = "Period")
Sales_Long
## Period variable value
## 1 1 Product_A 50
## 2 2 Product_A 53
## 3 3 Product_A 57
## 4 4 Product_A 59
## 5 5 Product_A 65
## 6 6 Product_A 67
## 7 7 Product_A 72
## 8 8 Product_A 76
## 9 9 Product_A 79
## 10 10 Product_A 83
## 11 11 Product_A 86
## 12 12 Product_A 93
## 13 13 Product_A 96
## 14 1 Product_B 62
## 15 2 Product_B 66
## 16 3 Product_B 72
## 17 4 Product_B 75
## 18 5 Product_B 79
## 19 6 Product_B 83
## 20 7 Product_B 88
## 21 8 Product_B 92
## 22 9 Product_B 96
## 23 10 Product_B 98
## 24 11 Product_B 102
## 25 12 Product_B 106
## 26 13 Product_B 109
colnames(Sales_Long)[2] <- "Product"
colnames(Sales_Long)[3] <- "Units_Sold"
# 3. Line graph -----------------------------------------------------------
library(ggplot2)
ggplot(data = Sales_Long, aes(x = Period, y = Units_Sold,
group = Product,
colour = Product)) +
geom_line() +
ylab("Number of units sold") +
scale_x_continuous(breaks = seq(min(Sales_Long$Period),
max(Sales_Long$Period), by = 2))
# 4. Indexed growth -------------------------------------------------------
Sales
## # A tibble: 13 x 3
## Period Product_A Product_B
## <dbl> <dbl> <dbl>
## 1 1 50 62
## 2 2 53 66
## 3 3 57 72
## 4 4 59 75
## 5 5 65 79
## 6 6 67 83
## 7 7 72 88
## 8 8 76 92
## 9 9 79 96
## 10 10 83 98
## 11 11 86 102
## 12 12 93 106
## 13 13 96 109
Sales$Product_A_Growth <- Sales$Product_A/50*100
Sales$Product_B_Growth <- Sales$Product_B/62*100
Sales
## # A tibble: 13 x 5
## Period Product_A Product_B Product_A_Growth Product_B_Growth
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 50 62 100 100.0000
## 2 2 53 66 106 106.4516
## 3 3 57 72 114 116.1290
## 4 4 59 75 118 120.9677
## 5 5 65 79 130 127.4194
## 6 6 67 83 134 133.8710
## 7 7 72 88 144 141.9355
## 8 8 76 92 152 148.3871
## 9 9 79 96 158 154.8387
## 10 10 83 98 166 158.0645
## 11 11 86 102 172 164.5161
## 12 12 93 106 186 170.9677
## 13 13 96 109 192 175.8065
names(Sales)
## [1] "Period" "Product_A" "Product_B"
## [4] "Product_A_Growth" "Product_B_Growth"
Sales_Growth <- subset(Sales, select = c("Period", "Product_A_Growth",
"Product_B_Growth"))
Sales_Growth
## # A tibble: 13 x 3
## Period Product_A_Growth Product_B_Growth
## <dbl> <dbl> <dbl>
## 1 1 100 100.0000
## 2 2 106 106.4516
## 3 3 114 116.1290
## 4 4 118 120.9677
## 5 5 130 127.4194
## 6 6 134 133.8710
## 7 7 144 141.9355
## 8 8 152 148.3871
## 9 9 158 154.8387
## 10 10 166 158.0645
## 11 11 172 164.5161
## 12 12 186 170.9677
## 13 13 192 175.8065
Sales_Growth_Long <- melt(Sales_Growth, id.vars = "Period")
Sales_Growth_Long
## Period variable value
## 1 1 Product_A_Growth 100.0000
## 2 2 Product_A_Growth 106.0000
## 3 3 Product_A_Growth 114.0000
## 4 4 Product_A_Growth 118.0000
## 5 5 Product_A_Growth 130.0000
## 6 6 Product_A_Growth 134.0000
## 7 7 Product_A_Growth 144.0000
## 8 8 Product_A_Growth 152.0000
## 9 9 Product_A_Growth 158.0000
## 10 10 Product_A_Growth 166.0000
## 11 11 Product_A_Growth 172.0000
## 12 12 Product_A_Growth 186.0000
## 13 13 Product_A_Growth 192.0000
## 14 1 Product_B_Growth 100.0000
## 15 2 Product_B_Growth 106.4516
## 16 3 Product_B_Growth 116.1290
## 17 4 Product_B_Growth 120.9677
## 18 5 Product_B_Growth 127.4194
## 19 6 Product_B_Growth 133.8710
## 20 7 Product_B_Growth 141.9355
## 21 8 Product_B_Growth 148.3871
## 22 9 Product_B_Growth 154.8387
## 23 10 Product_B_Growth 158.0645
## 24 11 Product_B_Growth 164.5161
## 25 12 Product_B_Growth 170.9677
## 26 13 Product_B_Growth 175.8065
colnames(Sales_Growth_Long)[2] <- "Product"
colnames(Sales_Growth_Long)[3] <- "Sales_Growth"
names(Sales_Growth_Long)
## [1] "Period" "Product" "Sales_Growth"
ggplot(Sales_Growth_Long, aes(x = Period, y = Sales_Growth,
group = Product,
colour = Product)) +
geom_line() +
ylab("Sales growth") +
scale_x_continuous(breaks = seq(min(Sales_Long$Period),
max(Sales_Long$Period), by = 2))
