Publications by Daniel Lee
NHL Skaters Stat 2022-23
Import data https://www.hockey-reference.com/leagues/NHL_2023_skaters.html#stats::goals # excel file NHL <- read_excel("../00_data/NHL_skaterStat_2022-23.xlsx") NHL # Remove column names in the middle of the dataset NHL State one question What age enables an NHL player to score more points than the others? # Plot data Plot data ggplot(dat...
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##Introduction ##Questions What type of variation occurs within my variables? What type of covariation occurs between my variables? Variation Visualizing distributions ggplot(data = diamonds) + geom_bar(mapping = aes(x = cut)) diamonds %>% count(cut) ## # A tibble: 5 × 2 ## cut n ## <ord> <int> ## 1 Fair 1610 ## 2 ...
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Apply 3
Import data # excel file data <- read_excel("data/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...
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title: “Week 9 : Code Analog 8” author: “Jak Jallah” date: “2023-01-13” output: html_document editor_options: chunk_output_type: console nycflights13 airlines ## # A tibble: 16 × 2 ## carrier name ## <chr> <chr> ## 1 9E Endeavor Air Inc. ## 2 AA American...
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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...
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Tidy Data Pivoting long to wide form table4a_long <- table4a %>% pivot_longer(cols = c('1999', '2000'), names_to = "year", values_to = "cases") Wide to long table4a_long %>% pivot_wider(names_from = year, values_from = cases) ## # A tibble: 3 × 3 ## country `1999` `2000` ## <chr> <in...
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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...
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Introduction nycflights13 Keys Mutating joins x <- tribble( ~key, ~val_x, 1, "x1", 2, "x2", 3, "x3" ) y <- tribble( ~key, ~val_y, 1, "y1", 2, "y2", 4, "y3" ) inner_join(x,y) ## Joining, by = "key" ## # A tibble: 2 × 3 ## key val_x val_y ## <dbl> <chr> <chr> ## 1 1 x1 y1 ## 2 2 x2 y2 O...
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Homework #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 ...
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Best Practices 1
Chapter 1 It’s Not Just about Forecasting The following are the key points in the chapter. Elaborate on each point in at least 30 words. Understanding economics can help you to diagnose the causes of increases or decreases in sales volumes and costs. Businomics is able to provide different tools that we would need to use to understand differe...
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