update for new post
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					 1 changed files with 53 additions and 2 deletions
				
			
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			@ -1,9 +1,60 @@
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# ---- Clean Environment ----
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rm(list = ls())
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# Load Packages
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# Load Packages ----
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box::use(
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  readr[read_csv],
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)
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# Load Data ----
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url <- "https://bit.ly/gacttCSV"
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ds_raw <- read_csv(url)
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# Count NAs ----
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nrow(ds_raw)
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na_count <- ds_raw |> 
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  dplyr::mutate(num_na = rowSums(is.na(ds))) |> 
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  dplyr::summarise(
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    n = dplyr::n(),
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    .by = num_na
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  )
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# don't show this in blog but note that I did it
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ds_raw |> 
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  dplyr::summarise(dplyr::across(dplyr::everything(), ~ sum(is.na(.)), .names = "{.col}")) |> 
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  tidyr::pivot_longer(tidyr::everything()) |> 
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  dplyr::arrange(desc(value)) |> 
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  print(n = 50)
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# Clean Data ----
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ds <- ds_raw |>
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  dplyr::select(
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    ID = `Submission ID`,
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    age = `What is your age?`,
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    cups = `How many cups of coffee do you typically drink per day?`,
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    where_drink = `Where do you typically drink coffee?`,
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    brew_method = `How do you brew coffee at home?`,
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    favorite = `What is your favorite coffee drink?`,
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    additions = `Do you usually add anything to your coffee?`,
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    style = `Before today's tasting, which of the following best described what kind of coffee you like?`,
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    strength = `How strong do you like your coffee?`,
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    roast_level = `What roast level of coffee do you prefer?`,
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    why_drink = `Why do you drink coffee?`,
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    taste = `Do you like the taste of coffee?`,
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    gender = Gender,
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    education_level = `Education Level`,
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    ethnicity = `Ethnicity/Race`,
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    employment = `Employment Status`,
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    political_view = `Political Affiliation`   
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  ) |> 
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  tidyr::drop_na()
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