Publications by Daniel Lee
Code Along 1
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 di...
1397 sym R (2742 sym/22 pcs) 17 img
codealong11
Goal is to automate building and tuning a classification model to predict employee attrition, using the h2o::h2o.automl. Set up Import data Import the cleaned data from Module 7. library(h2o) ## Warning: package 'h2o' was built under R version 4.3.3 ## ## ---------------------------------------------------------------------- ## ## Your next...
337 sym R (38321 sym/67 pcs)
codeapply11
library(h2o) ## Warning: package 'h2o' was built under R version 4.3.3 ## ## ---------------------------------------------------------------------- ## ## Your next step is to start H2O: ## > h2o.init() ## ## For H2O package documentation, ask for help: ## > ??h2o ## ## After starting H2O, you can use the Web UI at http://localh...
68 sym R (19109 sym/65 pcs)
codealong12
library(tidyverse) attrition_raw_tbl <- read_csv(“../00_data/WA_Fn-UseC_-HR-Employee-Attrition.csv”) If data is not sensitive: attrition_raw_tbl %>% glimpse() If data is sensitive: attrition_raw_tbl %>% slice(0) %>% glimpse() library(tidyverse) ## Warning: package 'ggplot2' was built under R version 4.3.2 ## ── Attaching core tidyverse p...
275 sym R (8107 sym/41 pcs)
intcodealong12
library(tidyverse) attrition_raw_tbl <- read_csv(“../00_data/WA_Fn-UseC_-HR-Employee-Attrition.csv”) If data is not sensitive: attrition_raw_tbl %>% glimpse() If data is sensitive: attrition_raw_tbl %>% slice(0) %>% glimpse() library(tidyverse) ## Warning: package 'ggplot2' was built under R version 4.3.2 ## ── Attaching core tidyverse p...
1448 sym R (8107 sym/41 pcs)
codeapply12
library(tidyverse) attrition_raw_tbl <- read_csv(“../00_data/WA_Fn-UseC_-HR-Employee-Attrition.csv”) If data is not sensitive: attrition_raw_tbl %>% glimpse() If data is sensitive: attrition_raw_tbl %>% slice(0) %>% glimpse() library(tidyverse) ## Warning: package 'ggplot2' was built under R version 4.3.2 ## ── Attaching core tidyverse p...
504 sym R (23119 sym/40 pcs)
Apply to your data 11
The goal is to automate building and tuning a classification model to predict employee attrition, using the h2o::h2o.automl. library(h2o) ## ## ---------------------------------------------------------------------- ## ## Your next step is to start H2O: ## > h2o.init() ## ## For H2O package documentation, ask for help: ## > ??h2o ## ## A...
369 sym R (61667 sym/56 pcs) 4 tbl
Code Along 12
Prompt 1: I have a dataset called attrition_raw_tbl that looks like this. library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.4.4 ✔ purrr 1.0.2 ## ✔ tibble 3.2.1 ✔ dplyr 1.1.4 #...
4047 sym R (14054 sym/26 pcs)
Apply to your data 12
library(readr) library(skimr) # Now, let's read the CSV file members <- read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/members.csv') ## Rows: 76519 Columns: 21 ## ── Column specification ───────────────────────────────────...
110 sym R (9747 sym/32 pcs) 4 tbl
Apply 9
Set up library(tidyverse) library(tidyquant) # for financial analysis library(broom) # for tidy model results library(umap) # for dimension reduction library(plotly) # for interactive visualization Data # Get info on companies listed in S&P500 sp500_index_tbl <- tq_index("SP500") # Get individual stocks from S&P500 sp500_symbols <- sp500_index_t...
1916 sym R (9565 sym/29 pcs) 4 img