Top 10 Regions of Russia for Alcohol Drinks Promotions
Based on my analysis of the provided dataset, I suggest the following top 10 regions for holding alcoholic promotions (also see the graph "Top 10 Regions in Russia with Highest Total Alcohol Drinks Consumption in Liters per Person from 1998 to 2016"): Moscow, Yamalo-Nenets Autonomous Okrug, Tyumen Oblast, Komi Republic, Khanty–Mansi Autonomous Okrug – Yugra, Chelyabinsk Oblast, Vologda Oblast, Sverdlovsk Oblast, Ivanovo Oblast, and Khabarovsk Krai.
My approach for predicting top 10 regions for alcohol drinks promotions is to assume that future trends in consumption of alcohol will follow the past. To select top 10 regions with highest total alcohol consumption, I have summarized consumption in liters of all categories of drinks during the total time indicated per region. St. Petersburg has been ranked as number 2 based on my data analysis, but I have excluded this region from my list due to previous analysis that already recommends this region for conducting promotions. Identification of St. Petersburg among top 10 hits using my approach serves as evidence for efficiency of my data analysis method.
Loading packages
library(tidyverse)
library(skimr)Importing data
data <- readr::read_csv('./data/russian_alcohol_consumption.csv')
print(data)Summarising total consumed alcohol in liters per region
data1 <- data %>%
filter(year %in% c(1998:2016)) %>%
group_by(region) %>%
summarize(wine_total = sum(wine),
beer_total = sum(beer),
vodka_total = sum(vodka),
champagne_total = sum(champagne),
brandy_total = sum(brandy)) %>%
mutate(alcohol_total = wine_total + beer_total
+ vodka_total + champagne_total + brandy_total)
print(data1)Selecting top 10 regions with most consumed total alcohol in liters
data2 <- data1 %>% select(region, alcohol_total) %>% group_by(region) %>% arrange(desc(alcohol_total)) print(data2)
Removing "Saint Petersburg" from the list
data3 <- head(data2, 11)
data4 <- data3[-2, ]
print(data4)Visualizing top 10 region with heighest alcohol consumption
analysis <- ggplot(data4, aes(x = alcohol_total, y = reorder(region, alcohol_total), color = alcohol_total)) +
geom_point(size = 14) +
geom_segment(aes(xend = 30, yend = region), size = 2) +
geom_text(aes(label = alcohol_total), color = "white", size = 3) +
scale_x_continuous("", expand = c(0,0), limits = c(0,2400), position = "top") +
labs(title = "Top 10 Regions in Russia with Highest
Total Alcohol Drinks Consumption
in Liters per Person from 1998 to 2016", caption = "Source: russian_alcohol_consumption")
top_10 <- analysis + theme_classic() +
theme(axis.line.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text = element_text(color = "black", size = 11),
axis.title = element_blank(),
legend.position = "none")
print(top_10)