Publications by Daniel Lee
Principles of Economics: Best Practice 9
Chapter Opening Questions A business manager, to assess the risk of a regional recession, needs to monitor Summary Although a regional economic cycle is not perfectly synchronized with its national counterpart, it tends to move up and down with the national economy. In addition to the broader national economy, two other factors influence a reg...
1558 sym 2 tbl
Principles of Economics: Best Practice 10
Chapter Opening Questions A business manager in a capital-intensive industry needs to monitor its own industry cycles because they routinely experience (). Summary Why capital-intensive industries are different Elements that make capital-intensive industries prone to overbuilding: high overhead long lead time to put new capacity in place low r...
1123 sym 2 tbl
Principles of Economics: Best Practice 3
Chater Openning Questions Managers need to know: Summary Causes of Recessions How it works Associated Recessions monetary policy The Fed can slow the economy by tightening monetary policy, which decreases the money supply and/or raises interest rates. Higher interests reduce economic activity by increasing financing costs. all recessions? The ...
2004 sym 1 tbl
Document
Import your data data <- read_excel("../00_data/myData.xlsx") ## New names: ## • `` -> `...1` data ## # A tibble: 4,810 × 24 ## ...1 rank position hand player years total…¹ status yr_st…² season age ## <dbl> <dbl> <chr> <chr> <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> ## 1 1 1 C Left Wayne G… 19...
362 sym
Apply 7: NHL seasonal goals
Import your data season_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/season_goals.csv') ## Rows: 4810 Columns: 23 ## ── Column specification ───────────────────────────────────────────�...
166 sym Python (3296 sym/11 pcs)
Document
Introduction String Basics chac_data <- "I'm 'very' hungry." stringr::str_length("I am hungry.") ## [1] 12 stringr::str_c(c("I", " am"), collapse = "") ## [1] "I am" stringr::str_c("I", " am", sep = " ;") ## [1] "I ; am" str_sort(c("John", "Mary", "Aaron")) ## [1] "Aaron" "John" "Mary" Matching patterns with regular expressions flights %>% gl...
364 sym
Document
Import your data data <- read_excel("../00_data/myData.xlsx") ## New names: ## • `` -> `...1` data ## # A tibble: 4,810 × 24 ## ...1 rank position hand player years total…¹ status yr_st…² season age ## <dbl> <dbl> <chr> <chr> <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> ## 1 1 1 C Left Wayne G… 19...
120 sym Python (14284 sym/22 pcs)
Apply to data 7
Import your data # excel file data <- read_excel("Chocolate.xlsx") data ## # A tibble: 191 × 10 ## https://www…¹ compa…² compa…³ revie…⁴ count…⁵ speci…⁶ cocoa…⁷ ingre…⁸ most_…⁹ ## <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> ## 1 2454 5150 U.S.A. 2019 Tanzan...
165 sym Python (6472 sym/10 pcs)
CA9
Introduction String Basics chac_data <- "I'm 'very' hungry." stringr::str_length("I am hungry") ## [1] 11 stringr::str_c(c("I", "am"), collapse = "") ## [1] "Iam" stringr::str_c("I", "am", sep = ";") ## [1] "I;am" str_sort(c("John", "Mary", "Aaron")) ## [1] "Aaron" "John" "Mary" Matching Patterns flights %>% glimpse() ## Rows: 336,776 ## Colu...
318 sym
Document
Import Data # excel file Chocolate <- read_excel("../00_data/Chocolate.xlsx") Chocolate ## # A tibble: 191 × 10 ## ref compan…¹ compa…² revie…³ count…⁴ speci…⁵ cocoa…⁶ ingre…⁷ most_…⁸ rating ## <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl> ## 1 2454 5150 U.S.A. 2019 T...
111 sym