View financial_taccount_ggplot
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library(tidyverse) | |
library(scales) | |
scrapy_stocks <- function(stock){ | |
if ("rvest" %in% installed.packages()) { | |
library(rvest) | |
}else{ | |
install.packages("rvest") | |
library(rvest) | |
} |
View fake_addresses
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library(tidyverse) | |
library(lubridate) | |
library(leaflet) | |
# https://www.fakenamegenerator.com/order.php | |
# go there to generate fake addresses, don't forget to select to include longitude and latitude | |
addresses <- read_csv("FakeNameGenerator.com_f201506b.csv") | |
addresses <- addresses %>% mutate(Birthday = mdy(Birthday), |
View pca2.R
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# What is PCA? | |
# - PCA is a form of multi-dimensional scaling. | |
# - It transforms the data into a lower dimensional space while keeping the maxiumum of information. | |
# Book: Multi-Dimensional Diversification | |
# get data https://www.msci.com/end-of-day-data-search | |
library(tidyverse) | |
library(tidyquant) | |
library(readxl) |
View treasury.R
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library(tidyquant) | |
ty10 <- tq_get("DGS10", get = "economic.data", from = as.Date("1950-01-01")) | |
mod_dur <- function(yield) { | |
# out <- (1-(1/(1+0.5*yield/100)^(2*10)))/(yield/100) | |
out <- (1-(1/(1+0.5*yield)^(2*10)))/(yield) | |
return(out) |
View get_earnings.R
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library(tidyverse) | |
library(jsonlite) | |
get_earnings <- function(symbol, av_key, get = "quarterly", cache_dir = "cache") { | |
if (!(cache_dir %in% list.dirs(full.names = F, recursive = F))) { | |
dir.create(cache_dir) | |
} | |
if (!(paste0(symbol, ".json") %in% list.files(cache_dir))) { | |
print("downloading") |
View SR_calc.R
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library(tidyverse) | |
library(tidyquant) | |
library(lubridate) | |
# get data from Yahoo ---- | |
spx <- tq_get("^GSPC") | |
# calculate returns ---- | |
ret_daily <- spx %>% | |
mutate(ret = adjusted/lag(adjusted)-1, |
View tabsetgetyoucrazy.R
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library(shiny) | |
ui <- fluidPage( | |
fluidRow( | |
column(width = 12, | |
tabsetPanel( | |
tabItem("main", "MENU"), | |
tabItem("more", uiOutput("hello")) | |
)) | |
) |
View app.R
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library(shiny) | |
library(shinyWidgets) | |
library(tidyverse) | |
# read persistent data or create a new file if it does not exist yet | |
if ("favs.csv" %in% list.files()) { | |
favs <- read_file("favs.csv") %>% | |
strsplit(", ") %>% | |
.[[1]] %>% | |
as.numeric() %>% |
View letf.R
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library(tidyverse) | |
library(ggplot2) | |
periods <- 10 | |
trend <- 0 | |
vola <- 0.1 | |
leverage <- 2 |
View persistent-tidy-data-shiny.R
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library(shiny) | |
library(tidyverse) | |
# data <- readRDS("persistent_data/data.RDS") | |
data <- as_tibble(mtcars) %>% head() | |
ui <- fluidPage( | |
tableOutput("mytable"), | |
actionButton("go", "filter it"), | |
actionButton("save", "save it") |
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