Publications by Mackenzie Labrie

Code Along 2

15.09.2023

This template offers an opinionated guide on how to structure a modeling analysis. Your individual modeling analysis may require you to add to, subtract from, or otherwise change this structure, but consider this a general framework to start from. If you want to learn more about using tidymodels, check out our Getting Started guide. In this example...

6460 sym R (6209 sym/31 pcs) 5 img

Apply 2

15.09.2023

This template offers an opinionated guide on how to structure a modeling analysis. Your individual modeling analysis may require you to add to, subtract from, or otherwise change this structure, but consider this a general framework to start from. If you want to learn more about using tidymodels, check out our Getting Started guide. In this example...

7842 sym R (6470 sym/31 pcs) 4 img

Apply 1

11.09.2023

library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.3 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0 ## ...

5045 sym R (11067 sym/46 pcs) 3 img 5 tbl

Code Along 1

09.09.2023

Explore data library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.3 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.2 ✔ tidyr ...

5195 sym R (7780 sym/39 pcs) 4 img

Test Publishing

20.09.2022

Do your work here. library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4 ## ✔ tibble 3.1.8 ✔ dplyr 1.0.10 ## ✔ tidyr 1.2.1 ✔ stringr 1.4.1 ## �...

26 sym R (1492 sym/4 pcs)

My Data Shedding Level Chart

23.09.2022

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4 sym 2 img

CodeAlong4

26.09.2022

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) ## ── Attaching packages ────────────...

1386 sym R (2513 sym/18 pcs) 10 img

Apply 4

29.09.2022

Import data # excel file data <- read_excel("../00_data/myData_charts.xlsx", sheet = "myData", skip = 1) ## New names: ## • `` -> `...1` data ## # A tibble: 195 × 18 ## ...1 Breed Affec…¹ Good …² Good …³ Shedd…⁴ Coat …⁵ Drool…⁶ Coat …⁷ Coat …⁸ ## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl...

751 sym 2 img

Code Along 5 CH4

02.10.2022

Coding basics R as a calculator assignment symbol 1000 / 10 ## [1] 100 x <- 1000 / 10 # x What’s in a name? Calling functions Use of TAB seq(from = 1, to = 10) ## [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 (222 sym/9 pcs)

Code Along 5 Chp 5

05.10.2022

Import data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_de…¹ dep_d…² arr_t…³ sched…⁴ arr_d…⁵ carrier ## <int> <int> <int> <int> <int> <dbl> <int> <int> <dbl> <chr> ## 1 2013 1 1 517 515 2 830 819 11 UA ## 2 2013 1 1 5...

339 sym Python (20370 sym/49 pcs) 1 img