Publications by Bella Kalinyak
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##Tidy data # Compute rate per 10,000 table1 %>% mutate(rate = cases / population * 10000) ## # A tibble: 6 × 5 ## country year cases population rate ## <chr> <dbl> <dbl> <dbl> <dbl> ## 1 Afghanistan 1999 745 19987071 0.373 ## 2 Afghanistan 2000 2666 20595360 1.29 ## 3 Brazil 1999 37737 17200636...
205 sym R (4852 sym/28 pcs) 1 img
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Import data data <- read_excel("../00_data/myData.xlsx") Introduction Questions Variation Visualizing distributions ggplot(data = data) + geom_bar(mapping = aes(x = food_category)) ggplot(data = data) + geom_histogram(mapping = aes(x = consumption)) ## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. ggplot(data = data...
309 sym 16 img
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Import data # excel file data <- read_excel("../00_data/myData.xlsx") data ## # A tibble: 1,430 × 4 ## country food_category consumption co2_emmission ## <chr> <chr> <dbl> <dbl> ## 1 Argentina Pork 10.5 37.2 ## 2 Argentina Poultry ...
165 sym Python (4396 sym/12 pcs)
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Introduction Questions Variation Visualizing distributions diamonds %>% ggplot(aes(x = cut)) + geom_bar() diamonds %>% ggplot(mapping = aes(x = carat)) + geom_histogram(binwidth = 0.5) diamonds %>% filter(carat < 3) %>% ggplot(aes(x = carat)) + geom_histogram(binwidth = 0.5) diamonds %>% ggplot(aes(...
294 sym R (2753 sym/25 pcs) 22 img
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Import data # excel file data <- read_excel("../00_data/myData.xlsx") data ## # A tibble: 1,430 × 4 ## country food_category consumption co2_emmission ## <chr> <chr> <dbl> <dbl> ## 1 Argentina Pork 10.5 37.2 ## 2 Argentina Poultry ...
159 sym Python (2729 sym/6 pcs)
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Import data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time ## <int> <int> <int> <int> <int> <dbl> <int> <int> ## 1 2013 1 1 517 515 2 830 819 ## 2 2013 1 1 533 529 ...
393 sym Python (33792 sym/88 pcs) 5 img
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Coding basics R as a calculator 1000/10 ## [1] 100 x <- 1000/10 #x assignment symbol What’s in a name? Calling functions Use of TAB seq(from = 1, to = 10, by = 1) ## [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 (226 sym/9 pcs)
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Import data # excel file data <- read_excel("../00_data/myData.xlsx") data ## # A tibble: 1,430 × 4 ## country food_category consumption co2_emmission ## <chr> <chr> <dbl> <dbl> ## 1 Argentina Pork 10.5 37.2 ## 2 Argentina Poultry ...
464 sym 1 img
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Import data # excel file data <- read_excel("data/myData.xlsx") data ## # A tibble: 1,430 × 4 ## country food_category consumption co2_emmission ## <chr> <chr> <dbl> <dbl> ## 1 Argentina Pork 10.5 37.2 ## 2 Argentina Poultry 3...
34 sym 1 img