Create data frame by iteratively adding rows - r

Question

I am trying to create a data frame (BOS.df) in order to explore the structure of a future analysis I will perform prior to receiving the actual data. In this scenario, lets say that there are 4 restaurants looking to run ad campaigns (the "Restaurant" variable). The total number of days that the campaign will last is cmp.lngth. I want random numbers for how much they are billing for the ads (ra.num). The ad campaigns start on StartDate. ultimately, I want to create a data frame the cycles through each restaurant, and adds a random billing number for each day of the ad campaign by adding rows.
#Create Data Placeholders
set.seed(123)
Restaurant <- c('B1', 'B2', 'B3', 'B4')
cmp.lngth <- 42
ra.num <- rnorm(cmp.lngth, mean = 100, sd = 10)
StartDate <- as.Date("2017-07-14")
BOS.df <- data.frame(matrix(NA, nrow =0, ncol = 3))
colnames(BOS.df) <- c("Restaurant", "Billings", "Date")
for(i in 1:length(Restaurant)){
for(z in 1:cmp.lngth){
BOS.row <- c(as.character(Restaurant[i]),ra.num[z],StartDate +
cmp.lngth[z]-1)
BOS.df <- rbind(BOS.df, BOS.row)
}
}
My code is not functioning correctly right now. The column names are incorrect, and the data is not being placed correctly if at all. The output comes through as follows:
X.B1. X.94.3952435344779. X.17402.
1 B1 94.3952435344779 17402
2 B1 <NA> <NA>
3 B1 <NA> <NA>
4 B1 <NA> <NA>
5 B1 <NA> <NA>
6 B1 <NA> <NA>
How can I obtain the correct output? Is there a more efficient way than using a for loop?

Answer 1

Using expand.grid:
cmp.lngth <- 2
StartDate <- as.Date("2017-07-14")
set.seed(1)
df1 <- data.frame(expand.grid(Restaurant, seq(cmp.lngth) + StartDate))
colnames(df1) <- c("Restaurant", "Date")
df1$Billings <- rnorm(nrow(df1), mean = 100, sd = 10)
df1 <- df1[ order(df1$Restaurant, df1$Date), ]
df1
# Restaurant Date Billings
# 1 B1 2017-07-15 93.73546
# 5 B1 2017-07-16 103.29508
# 2 B2 2017-07-15 101.83643
# 6 B2 2017-07-16 91.79532
# 3 B3 2017-07-15 91.64371
# 7 B3 2017-07-16 104.87429
# 4 B4 2017-07-15 115.95281
# 8 B4 2017-07-16 107.38325

Answer 2

You can use rbind, but this would be another way to do it.
Also, the length of the data frame should be cmp.lngth*length(Restaurant), not cmp.lngth.
#Create Data Placeholders
set.seed(123)
Restaurant <- c('B1', 'B2', 'B3', 'B4')
cmp.lngth <- 42
ra.num <- rnorm(cmp.lngth, mean = 100, sd = 10)
StartDate <- as.Date("2017-07-14")
BOS.df <- data.frame(matrix(NA, nrow = cmp.lngth*length(Restaurant), ncol = 3))
colnames(BOS.df) <- c("Restaurant", "Billings", "Date")
count <- 1
for(name in Restaurant){
for(z in 1:cmp.lngth){
BOS.row <- c(name, ra.num[z], as.character(StartDate + z - 1))
BOS.df[count,] <- BOS.row
count <- count + 1
}
}
I would also recommend you to look at the package called tidyverse and use add_row with tibble instead of data frame. Here is a sample code:
library(tidyverse)
BOS.tb <- tibble(Restaurant = character(),
Billings = numeric(),
Date = character())
for(name in Restaurant){
for(z in 1:cmp.lngth){
BOS.row <- c(name, ra.num[z], as.character(StartDate + z - 1))
BOS.tb <- add_row(BOS.tb,
Restaurant = name,
Billings = ra.num[z],
Date = as.character(StartDate + z - 1))
}
}