R barplot cumulative - x date, y freq - r

Question

I'm trying to recreate this kind of plot in R but I'm not very successful.
Where X = date and Y = frequency of a discrete variable, cumulative on one bar.
Also I'm trying to put it in a function so it would be easier to use this kind of plot for different variables.
Link to the plot image <---
I'd appreciate any help!
Data example:
Excel plot example <---
Purchase_date Phone
2014-10-23 Sony
2014-10-23 Apple
2014-10-23 Nokia
2014-10-23 Nokia
2014-10-24 NA
2014-10-24 Nokia
2014-10-24 Sony
2014-10-24 Other
2014-10-24 Apple
2014-10-25 Sony
2014-10-25 NA
2014-10-25 Apple
2014-10-25 Sony
2014-10-25 Nokia
Also
I have something like this but it's definitely far from universal method for different variables:
base_table %>%
filter(year(as.Date(BUY_DATE)) >= 2014, year(as.Date(BUY_DATE)) <= 2017) %>%
mutate(BUY_DATE = as.yearmon(as.Date(BUY_DATE))) %>%
group_by(PHONETYPE, BUY_DATE) %>% summarise(n = n()) -> applPerTypeAndMonth
applPerTypeAndMonth %>% pull(PHONETYPE) %>% table()
filter(applPerTypeAndMonth, PHONETYPE == '') -> x
xts(x$n, order.by = x$BUY_DATE) -> type1
filter(applPerTypeAndMonth, PHONETYPE == 'NOKIA') -> x
xts(x$n, order.by = x$BUY_DATE) -> type2
filter(applPerTypeAndMonth, PHONETYPE == 'APPLE') -> x
xts(x$n, order.by = x$BUY_DATE) -> type3
filter(applPerTypeAndMonth, PHONETYPE == 'SONY') -> x
xts(x$n, order.by = x$BUY_DATE) -> type4
filter(applPerTypeAndMonth, PHONETYPE == 'HUAWEI') -> x
xts(x$n, order.by = x$BUY_DATE) -> type5
filter(applPerTypeAndMonth, PHONETYPE == 'LG') -> x
xts(x$n, order.by = x$BUY_DATE) -> type6
filter(applPerTypeAndMonth, PHONETYPE == 'OTHER') -> x
xts(x$n, order.by = x$BUY_DATE) -> type7
merge(type1,type2,type3,type4,type5,type6,type7) -> types
na.fill(types, fill = 0.0) -> types
barplot(types, col = rainbow(7))
types %>% apply(1, function(x) x / sum(x)) %>% barplot(col = rainbow(7))
# legend("topright", legend = names(types), fill = rainbow(7))

Answer 1

Using data.table first create a summary table that details the frequency of each phone by each day.
summary = purchases[,list(Purchases = .N), by = list(Purchase_date, Phone)
Then split this out by phone type, and in each sub-dataset order by date and add in a cumulative purchases variable.
splitted = split(summary, summary$Phone)
splitted = lapply(splitted, function(x){
x = x[order(PurchaseDate)]
x$CumulativePurchases = cumsum(x$Purchases)
return(x)})
Then rbindlist back together into a single dataframe and then you can use GGplot easily.
summary = rbindlist(splitted)
plotted = ggplot(summary, aes(x = PurchaseDate, y = CumulativePurchases, fill = Phone)) + geom_bar(stat = "identity")

Answer 2

something along the lines of this,
dta <- structure(list(Purchase_date = structure(c(1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L), .Label = c("2014-10-23",
"2014-10-24", "2014-10-25"), class = "factor"), Phone = structure(c(4L,
1L, 2L, 2L, NA, 2L, 4L, 3L, 1L, 4L, NA, 1L, 4L, 2L), .Label = c("Apple",
"Nokia", "Other", "Sony"), class = "factor")), .Names = c("Purchase_date",
"Phone"), class = "data.frame", row.names = c(NA, -14L))
# install.packages(c("ggplot2"), dependencies = TRUE)
library(ggplot2)
g <- ggplot(dta, aes(Purchase_date))
g + geom_bar(aes(fill = Phone))
updated, here's the plot wrapped in a function,
function.name <- function(df)
{
require(ggplot2)
p <- ggplot(df, aes(x = Purchase_date))
p + geom_bar(aes(fill = Phone))
}
function.name(dta)
I'll obviously recommend you take a look at this site to learn how to label, color, reorder, etc.

Answer 3

# load packages
library(tidyverse)
library(lubridate)
# create a dataframe from your data
df <- frame_data(
~Purchase_date, ~Phone
, "2014-10-23", "Sony"
, "2014-10-23", "Apple"
, "2014-10-23", "Nokia"
, "2014-10-23", "Nokia"
, "2014-10-24", "NA"
, "2014-10-24", "Nokia"
, "2014-10-24", "Sony"
, "2014-10-24", "Other"
, "2014-10-24", "Apple"
, "2014-10-25", "Sony"
, "2014-10-25", NA
, "2014-10-25", "Apple"
, "2014-10-25", "Sony"
, "2014-10-25", "Nokia"
)
# make dates dates, if you want to
df <- df %>%
mutate(Purchase_date = as_date(Purchase_date))
# and plot it
df %>%
ggplot(aes(Purchase_date, fill = Phone)) +
geom_bar()
ggplot() and geom_bar() ARE a functions and they do what you want (and actually a whole lot more if desired). How to plot can be read up, e.g., in the R-Graphics Cookbook which really helps whenever you need it.