Tadge-Analytics

setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
library(tidyverse)
library(kableExtra)

formatted_Values <- tibble::tribble(
  ~Metric, ~BAKER, ~OREGON, ~RURAL, ~URBAN,
  "Food insecurity",  "15%",   "13%",     NA,     NA,
  "Child Poverty",  "23%",   "19%",  "18%",  "20%",
  "Foster care rate (per 1,000 population)",   "33",    "13",   "21",   "11",
  "Index crime (per 1,000 population)",   "20",    "30",   "20",   "32",

Tadge-Analytics

---
title: "Expense Analyser"
output: 
  flexdashboard::flex_dashboard:
    navbar:
      - { title: "About", href: "https://www.tadge-analytics.com.au", align: right }
runtime: shiny
---

```{r setup, include=FALSE}

Tadge-Analytics

# first, run the gist at:
# https://gist.github.com/Tadge-Analytics/63f75895f0b2e76dae60c1bd5ce8fec7

library(tidyverse)

vcglr_data <- readRDS("rds files/vcglr_data.rds")

    
# same location for start and end  
# note there cannot be a Licence Num (in the VCGLR) that is 1 or 2

Tadge-Analytics

# We also want to identify services stations which are the same... 
# but where the address is written differently
# in a way not corrected for, above...


unique_stations %>%
  distinct(full_name, new_address) %>%
  group_by(full_name) %>%
  mutate(rank = row_number()) %>%
  spread(rank, new_address) %>%

Tadge-Analytics

setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
library(tidyverse)


# data can be downloaded from:
# https://www.dropbox.com/s/odg6udrhahsqhiz/SydneyFuelPriceHistory.zip?dl=1



first_changes <- read_csv("data/SydneyFuelPriceHistory.csv") %>% 

Tadge-Analytics

library(tidyverse)

# Let's generate our different trials data
# and save to rds

test_if_sameness <- function(size_of_group) {
  tibble(person_id = 1:size_of_group) %>% 
    mutate(birthday = sample(1:365, n(), replace = T)) %>% 
    mutate(other_dates = list(rename(., person_id1 = person_id,
                                     birthday1 = birthday))) %>% 

Tadge-Analytics

Dates = 
VAR Days = CALENDAR(MIN('Order'[Order Date]), MAX('Order'[Order Date]) )
RETURN ADDCOLUMNS (
    Days,
    "Year", YEAR ( [Date] ),
    "Month Number", MONTH ( [Date] ),
    "Month", FORMAT ( [Date], "mmmm" ),
    "Year Month Number", YEAR ( [Date] ) * 12 + MONTH ( [Date] ) - 1,
    "Year Month", FORMAT ( [Date], "mmm yy" ),
    "DayOfWeekNumber", WEEKDAY ( [Date] ),

Tadge-Analytics

library(tidyverse)
library(httr)

# retrieve the data from the web

url <- "https://www.vcglr.vic.gov.au/sites/default/files/current_victorian_licences_by_location_august_2019.xlsx"
GET(url, write_disk(tf <- tempfile(fileext = ".xlsx")))
downloaded_data <- readxl::read_excel(tf, col_names = F, col_types = "text") 

Tadge-Analytics

library(dplyr)
library(magrittr)

library(Rserve)
Rserve(port = 1234)



process_data <- function(data) {

Tadge-Analytics

library(tidyverse)
library(gmailr)

# authorise gmailr

search_term <- "from:([email protected]) new jobs for tableau in Melbourne"
messageIDs <- messages(search = search_term, num_results = 5)

my_messages <- tibble(messageIDs) %>% 
  mutate(downloaded_data = map(messageIDs, ~.x$messages %>%