R script visual error for apriori

MAAbdullah47 — Sun, 09 Jul 2017 12:01:43 GMT

Dear All, I'm Trying to put the following code Inside R script visual:

#############################

library(arules)
library(Rsenal)
library(tidyverse)
#### Assignment of column names ####
setwd("C:/Users/XXXXXX/Data Worked")
## assigning column names to variables to help with filtering with NSE
day_of_the_week <- "day_of_the_week"
order_month <- "order_month"
order_year <- "order_year"
day_of_the_month <- "day_of_the_month"
order_hour <- "order_hour"
order_day_part <- "order_day_part"
order_month_n <- "order_month_n"
order_date <- "Order Date"#"order_business_date" #Order Date
#order_open <- "order_opened_at" #orders.opened_at
order_open <- "orders.opened_at" #orders.opened_at
#transaction_id <- "order_guid" #orders.guid
transaction_id <- "orders.guid" #orders.guid
#product_names <- "product_name_en" #products.name_en
product_names <- "Product" #products.name_en , branches.name_en
#branch_name <- "Branch"
branch_name <- "Branch"
oerder_tyep <-"Order_Type"
#product_sale_quantities <- "product_quantity" ,orders.products.quantity
product_sale_quantities <- "orders.products.quantity"

# End of Column Name assignments #

#### Feature generation ####

dd <- weekdays(as.Date(dataset[,order_date]))
dataset$day_of_the_week <- dd

## year of the order is added

YY <- format(as.Date(dataset[,order_date], format="%Y-%m-%d"),"%Y")
dataset$order_year<- YY

## order month is added to the data.
mm<-format(as.Date(dataset[,order_date], format="%Y-%m-%d"),"%m")
dataset$order_month <- mm

bb<-format(as.Date(dataset[,order_date], format="%Y-%m-%d"),"%b")
dataset$order_month_n <- bb

## order day of the month is added
dom <- format(as.Date(dataset[,order_date], format="%Y-%m-%d"),"%d")
dataset$day_of_the_month <- dom

## order hour is added orders.opened_at
hour<- format(strptime(dataset[, order_open], format="%Y-%m-%d %H:%M:%S"),"%H")
#hour<- format(strptime(dataset[, orders.opened_at], format="%Y-%m-%d %H:%M:%S"),"%H")

dataset$order_hour <- as.numeric(hour)
dataset$order_day_part <- ifelse(dataset$order_hour >= 6 & dataset$order_hour <= 10, "Morning(06:00 to 10:00)",
ifelse(dataset$order_hour >= 11 & dataset$order_hour <= 15, "Afternoon(11:00 to 15:00)",
ifelse(dataset$order_hour >= 16 & dataset$order_hour <= 20, "Evening(16:00 to 20:00)",
ifelse(dataset$order_hour >= 21, "Night(21:00 to 24:00)",
"Midnight(00:00 to 06:00)"))))

dataset$order_day_part <- ordered(dataset$order_day_part, levels = c("Midnight(00:00 to 06:00)", "Morning(06:00 to 10:00)",
"Afternoon(11:00 to 15:00)", "Evening(16:00 to 20:00)",
"Night(21:00 to 24:00)"))

order_string <- as.character(transaction_id)
product_string <- as.character(product_names)

dataset1 <- select_(dataset, transaction_id, product_names, branch_name, product_sale_quantities,
day_of_the_week, order_month, order_year, day_of_the_month, order_day_part,
order_month_n)

# Feature generation end #

#### Possible filter values ####
day <- as.list(c("All", sort(unique(as.character(dataset1[,day_of_the_week])))))
branch <- as.list(c("All", sort(unique(as.character(dataset1[,branch_name])))))
month <- as.list(c("All", sort(unique(dataset1[,order_month_n]))))
year <- as.list(c("All", sort(unique(dataset1[,order_year]))))
# Possible filter values end #

#### Filter area #####
day_filter <- "All"
branch_filter <- "All"
month_filter <- "All"
year_filter <- "All"
# Filter area end #

#### Filter operation start ####
if(day_filter %in% c("All") & branch_filter %in% c("All") & month_filter %in% c("All") & year_filter %in% c("All")){

dataset <- as(split(dataset1[,product_string], dataset1[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter != "All" & month_filter %in% c("All") & year_filter %in% c("All")){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part))
trans <- filter_(trans, lazyeval::interp(~var == branch_filter, var = as.name(branch_name)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter == "All" & month_filter != "All" & year_filter %in% c("All")){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
order_month, as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~var == month_filter, var = as.name(order_month_n)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter == "All" & month_filter == "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~var == year_filter, var = as.name(order_year)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter != "All" & month_filter == "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~var == year_filter, var = as.name(order_year)),
lazyeval::interp(~var == branch_filter, var = as.name(branch_name)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter != "All" & month_filter != "All" & year_filter %in% c("All")){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter == "All" & month_filter != "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == year_filter, var = as.name(order_year)),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter %in% c("All") & branch_filter != "All" & month_filter != "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == year_filter, var = as.name(order_year)),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))),
lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter == "All" & month_filter != "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))),
lazyeval::interp(~ var == year_filter, var = as.name(order_year)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter == "All" & month_filter != "All" & year_filter == "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter == "All" & month_filter == "All" & year_filter == "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter == "All" & month_filter == "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part))
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == year_filter, var = as.name(order_year)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter != "All" & month_filter == "All" & year_filter == "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part))
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter != "All" & month_filter == "All" & year_filter != "All"){

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)),
lazyeval::interp(~ var == year_filter, var = as.name(order_year)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else if(day_filter != "All" & branch_filter != "All" & month_filter != "All" & year_filter == "All") {

trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

} else {
trans <- select_(dataset1, transaction_id, product_names, branch_name, as.character(day_of_the_week),
as.character(order_month), as.character(order_year), as.character(order_day_part),
order_month_n)
trans <- filter_(trans, lazyeval::interp(~ var == day_filter, var = as.name(as.character(day_of_the_week))),
lazyeval::interp(~ var == branch_filter, var = as.name(branch_name)),
lazyeval::interp(~ var == month_filter, var = as.name(as.character(order_month_n))),
lazyeval::interp(~ var == year_filter, var = as.name(order_year)))

dataset <- as(split(trans[,product_string], trans[,order_string]), "transactions")

}

############################# From Alih
# arAll <- apriori(dataset, parameter=list(support = 0.001, confidence = 0.001,
# minlen = 2))
#
# Orders_Basket_Table <- inspect(sort(arAll, by = "confidence"),
# ruleSep = "", setStart = "",
# setEnd = "")
#############################

#rules_1 <- apriori(reports,parameter = list(supp = 0.001, conf = 0.001, target = "rules"))
rules_1 <- apriori(dataset,parameter = list(supp = 0.001, conf = 0.001, target = "rules"))
t =data.frame( lhs = labels( lhs(rules_1) ),
rhs = labels( rhs(rules_1) ),
quality(rules_1) )

#t = inspect(head(sort(rules, by ="support"),15))
#t = inspect(sort(rules_1, by ="support"))
#############
t$rhs<-as.character(t$rhs)
t$lhs<-as.character(t$lhs)
t$rhs<-gsub("{", "", t$rhs,fixed="TRUE")
t$rhs<-gsub("}", "", t$rhs,fixed="TRUE")
t$lhs<-gsub("{", "", t$lhs,fixed="TRUE")
t$lhs<-gsub("}", "", t$lhs,fixed="TRUE")
t$No_Of_LHS<- rowSums(t== ",")
x <- t$lhs
t$No_Of_LHS<-sapply(regmatches(x, gregexpr(",", x)), length)+1
t$LHS_Start_With <- gsub("^(.*?),.*", "\\1", t$lhs)
write.csv(t,"Orders_Basket_Table_1.csv")
##############data table
# rules_dt <- data.table( lhs = labels( lhs(rules_1) ),
# rhs = labels( rhs(rules_1) ),
# quality(rules_1) )[ order(-lift), ]
#
# # XX<-data.frame( lhs = labels( lhs(rules) ),
# # rhs = labels( rhs(rules) ),
# # quality(rules) )
#
# DT::datatable(rules_dt)
# #write.csv(dataset,"setting.csv")
############
par(mar = c(0,0,0,0))
plot(c(0, 0), c(0, 0))
if (is.null(t)) {
t = data.frame("no rules found")
text(x = 0.5, y = 0.5, paste("No Rules found"),
cex = 1.6, col = "black")
} else {
addtable2plot(-1, -1, t, bty = "n", display.rownames = F, hlines = F,
vlines = F)
}

###########################

When I Run this script in power bi I got errors (please refer to the image errors attached with this message).

Re: R script visual error for apriori

v-viig — Mon, 10 Jul 2017 07:03:14 GMT

Hello @MAAbdullah47,

Can you send description of this issue to pbicvsupport@microsoft.com?

We'll include our R developer to address the issue.

Ignat Vilesov,

Software Engineer

Microsoft Power BI Custom Visuals

pbicvsupport@microsoft.com

Re: R script visual error for apriori

MAAbdullah47 — Mon, 10 Jul 2017 07:20:30 GMT

Ok, The email I'll send from is: m.mubarah@quantda.net.

Re: R script visual error for apriori

MAAbdullah47 — Mon, 10 Jul 2017 07:21:12 GMT

So save my email (m.mubarah@quantda.net)

Re: R script visual error for apriori

Anonymous — Fri, 14 Jul 2017 21:14:12 GMT

I got a similar error too - any solutions for this?

Re: R script visual error for apriori

MAAbdullah47 — Sat, 15 Jul 2017 15:36:34 GMT

Ok I'll send you the email tomorrow.

Re: R script visual error for apriori

v-viig — Mon, 17 Jul 2017 12:45:05 GMT

Hello @Anonymous,

Please send an email to pbicvsupport@microsoft.com with error details.

We'll look into this issue.

Ignat Vilesov,

Software Engineer

Microsoft Power BI Custom Visuals

pbicvsupport@microsoft.com

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R script visual error for apriori

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