Publications by Daniel Lee
Document
Import stock prices stocks <- tq_get(c("NDA-FI.HE", "JPM", "DNB.OL", "MS"), get = "stock.prices", from = "2016-01-01") stocks ## # A tibble: 8,745 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 NDA-FI.HE 2016-01-04 1...
206 sym Python (6711 sym/21 pcs) 1 img
Apply it to your data 2
Import stock prices stocks <- tq_get(c("JNJ", "KSS", "TDS"), get = "stock.prices", from = "2017-01-01", to = "2019-01-01") stocks ## # A tibble: 1,506 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 JNJ ...
202 sym Python (5107 sym/16 pcs) 1 img
Document
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...
188 sym
apply it 2
Import stock prices stocks <- tq_get(c("COIN", "CMG", "U", "RIOT"), get = "stock.prices", from = "2016-01-01") stocks ## # A tibble: 6,170 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 COIN 2021-04-14 381 430...
203 sym Python (5514 sym/17 pcs) 1 img
Code Along 2 pt1
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)
Code Along 1
Goal: to predict the rental market prices in the SF rental market Click here for the data. Import Data rent <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-07-05/rent.csv') skimr::skim(rent) Data summary Name rent Number of rows 200796 Number of columns 17 _______________________ Colum...
314 sym 4 img 3 tbl
chp5
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 ...
548 sym Python (20182 sym/51 pcs) 1 img
Document
Import stock prices stocks <- tq_get(c("CMG", "GM", "LULU"), get = "stock.prices", from = "2016-01-01", ) stocks ## # A tibble: 6,552 × 8 ## symbol date open high low close volume adjusted ## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 CMG 2016-0...
50 sym Python (1103 sym/3 pcs) 1 img
Code Along 2 Ch5
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 ...
329 sym Python (19999 sym/49 pcs) 1 img
Document
Welcome Ch1 Introduction The data science project workflow Prerequisites R RStudio r packages Install the tidyverse package Running R code 1+2 ## [1] 3 Getting help Google Stackoverflow Ch2 Introduction to Data Exploration Ch3 Data Visualization Set up library(tidyverse) data mpg ## # A tibble: 234 × 11 ## manufacturer model d...
1351 sym R (1816 sym/9 pcs) 3 img