Publications by Bella Kalinyak
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library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1...
2059 sym R (18316 sym/35 pcs)
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# Load packages # Core library(tidyverse) library(tidyquant) # Source function source("../00_scripts/simulate_accumulation") 1 Import stock prices Revise the code below. Replace symbols with your stocks. Replace the from and the to arguments to date from 2012-12-31 to present. symbols <- c("TM", "SBUX", "AEO", "BBW") prices <- tq_get(x...
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library(tidymodels) ## ── Attaching packages ────────────────────────────────────── tidymodels 1.2.0 ── ## ✔ broom 1.0.7 ✔ recipes 1.0.10 ## ✔ dials 1.3.0 ✔ rsample 1.2.1 ## ✔ dplyr 1.1.4 ✔ tibble 3....
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# Load packages # Core library(tidyverse) library(tidyquant) # time series library(timetk) Goal Simulate future portfolio returns five stocks: “SPY”, “EFA”, “IJS”, “EEM”, “AGG” market: “SPY” from 2012-12-31 to 2017-12-31 1 Import stock prices symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG") prices <- tq_get(x = ...
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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) ## ## ---------------------------------------------------------------------- ## ## Your next step is to start H2O: ## > h2o.init() ## ## For H...
362 sym R (38068 sym/59 pcs)
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# Load packages # Core library(tidyverse) library(tidyquant) library(readr) # Time series library(lubridate) library(tibbletime) # modeling library(broom) Goal Examine how each asset contributes to portfolio standard deviation. This is to ensure that our risk is not concentrated in any one asset. 1 Import stock prices Chpppse your s...
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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) ## ## ---------------------------------------------------------------------- ## ## Your next step is to start H2O: ## > h2o.init() ## ## For H...
355 sym R (34260 sym/52 pcs)
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# Load packages # Core library(tidyverse) library(tidyquant) library(readr) # Time series library(lubridate) library(tibbletime) # modeling library(broom) Goal Examine how each asset contributes to portfolio standard deviation. This is to ensure that our risk is not concentrated in any one asset. five stocks: “SPY”, “EFA”, �...
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Import your data data(flights) flights %>% skimr::skim() Data summary Name Piped data Number of rows 336776 Number of columns 19 _______________________ Column type frequency: character 4 numeric 14 POSIXct 1 ________________________ Group variables None Variable type: character skim_variable n_missing complete_rate min max empty n_u...
531 sym Python (2837 sym/24 pcs) 4 tbl
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# for Core packages library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ...
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