Publications by Daniel Lee
Document
Import stock prices stocks <- tq_get(c("CMG", "GM", "LULU"), get = "stock.prices", from = "2016-01-01", ) stocks ## # A tibble: 6,567 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 CMG 2016-0...
189 sym Python (2877 sym/7 pcs) 1 img
Document
Import data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time ## <int> <int> <int> <int> <int> <dbl> <int> <int> ## 1 2013 1 1 517 515 2 830 819 ## 2 2013 1 1 533 529 ...
386 sym Python (18745 sym/49 pcs) 1 img
Document
Import stock prices stocks <- tq_get(c("PYPL", "GM", "ABNB", "AXP", "NVDA", "GOOGL"), get = "stock.prices", from = "2016-01-01") stocks ## # A tibble: 11,890 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 PYPL 2...
200 sym Python (5512 sym/17 pcs) 1 img
Code Along 2 - Part 2
Import Data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time ## <int> <int> <int> <int> <int> <dbl> <int> <int> ## 1 2013 1 1 517 515 2 830 819 ## 2 2013 1 1 533 529 ...
496 sym Python (19217 sym/48 pcs) 1 img
Code Along 2 - 1
Coding basics R as a calculator 1000 / 10 ## [1] 100 x <- 1000 / 10 # x assignment symbol What’s in a name? Calling functions Use of TAB seq(from = 1, to = 10, by = 1) ## [1] 1 2 3 4 5 6 7 8 9 10 continuation character, + seq(from = 1, to = 10) ## [1] 1 2 3 4 5 6 7 8 9 10 Printing to screen y <- seq(from = 1, to = 10) y...
171 sym Python (229 sym/9 pcs)
Apply1
Goal: to predict the price. Click [here for the data]https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-11-03/readme.md. Import Data ikea <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-11-03/ikea.csv') skimr::skim(ikea) Data summary Name ikea Number of rows 3694 N...
331 sym 4 img 4 tbl
Apply Data 2
Import stock prices stocks <- tq_get(c("SPOT", "ISRG", "KHC", "FIS", "GOOG"), get = "stock.prices", from = "2020-01-01",) stocks ## # A tibble: 5,900 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 SPOT 2020-01-02 ...
266 sym Python (5727 sym/14 pcs) 1 img
Code Along 2 pt 2
Import data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time ## <int> <int> <int> <int> <int> <dbl> <int> <int> ## 1 2013 1 1 517 515 2 830 819 ## 2 2013 1 1 533 529 ...
539 sym Python (19602 sym/49 pcs) 1 img
Apply 2 FA
Import stock prices stocks <- tq_get(c("NKE", "COKE", "ULTA", "AMZN", "AAPL"), get = "stock.prices", from = "2016-01-01") stocks ## # A tibble: 10,930 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 NKE 2016-01-04 61....
211 sym Python (9214 sym/25 pcs) 1 img