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E x ploring n u merical data E XP L OR ATOR Y DATA AN ALYSIS IN R Andre w Bra y Assistant Professor , Reed College Cars dataset str(cars) Classes tbl_df, tbl and 'data.frame': 428 obs. of 19 variables: $ name : chr

  1. E x ploring n u merical data E XP L OR ATOR Y DATA AN ALYSIS IN R Andre w Bra y Assistant Professor , Reed College

  2. Cars dataset str(cars) Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 428 obs. of 19 variables: $ name : chr "Chevrolet Aveo 4dr" "Chevrolet Aveo LS 4dr hatch" ... $ sports_car : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ suv : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ wagon : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ minivan : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ pickup : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ all_wheel : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ rear_wheel : logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ msrp : int 11690 12585 14610 14810 16385 13670 15040 13270 ... $ dealer_cost: int 10965 11802 13697 13884 15357 12849 14086 12482 ... $ eng_size : num 1.6 1.6 2.2 2.2 2.2 2 2 2 2 2 ... $ ncyl : int 4 4 4 4 4 4 4 4 4 4 ... $ horsepwr : int 103 103 140 140 140 132 132 130 110 130 ... $ city_mpg : int 28 28 26 26 26 29 29 26 27 26 ... $ hwy_mpg : int 34 34 37 37 37 36 36 33 36 33 ... $ weight : int 2370 2348 2617 2676 2617 2581 2626 2612 2606 ... $ wheel_base : int 98 98 104 104 104 105 105 103 103 103 ... $ length : int 167 153 183 183 183 174 174 168 168 168 ... $ width : int 66 66 69 68 69 67 67 67 67 67 ... EXPLORATORY DATA ANALYSIS IN R

  3. Dotplot ggplot(data, aes(x = weight)) + geom_dotplot(dotsize = 0.4) EXPLORATORY DATA ANALYSIS IN R

  4. Histogram ggplot(data, aes(x = weight)) + geom_histogram() EXPLORATORY DATA ANALYSIS IN R

  5. Densit y plot ggplot(data, aes(x = weight)) + geom_density() EXPLORATORY DATA ANALYSIS IN R

  6. Densit y plot ggplot(data, aes(x = weight)) + geom_density() EXPLORATORY DATA ANALYSIS IN R

  7. Densit y plot ggplot(data, aes(x = weight)) + geom_density() EXPLORATORY DATA ANALYSIS IN R

  8. Bo x plot ggplot(data, aes(x = 1, y = weight)) + geom_boxplot() + coord_flip() EXPLORATORY DATA ANALYSIS IN R

  9. Bo x plot ggplot(data, aes(x = 1, y = weight)) + geom_boxplot() + coord_flip() EXPLORATORY DATA ANALYSIS IN R

  10. Bo x plot ggplot(data, aes(x = 1, y = weight)) + geom_boxplot() + coord_flip() EXPLORATORY DATA ANALYSIS IN R

  11. Bo x plot ggplot(data, aes(x = 1, y = weight)) + geom_boxplot() + coord_flip() EXPLORATORY DATA ANALYSIS IN R

  12. Faceted histogram ggplot(cars, aes(x = hwy_mpg)) + geom_histogram() + facet_wrap(~pickup) `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. Warning message: Removed 14 rows containing non-finite values (stat_bin). EXPLORATORY DATA ANALYSIS IN R

  13. Faceted histogram ggplot(cars, aes(x = hwy_mpg)) + geom_histogram() + facet_wrap(~pickup) `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. Warning message: Removed 14 rows containing non-finite values (stat_bin). EXPLORATORY DATA ANALYSIS IN R

  14. Faceted histogram ggplot(cars, aes(x = hwy_mpg)) + geom_histogram() + facet_wrap(~pickup) `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. Warning message: Removed 14 rows containing non-finite values (stat_bin). EXPLORATORY DATA ANALYSIS IN R

  15. Let ' s practice ! E XP L OR ATOR Y DATA AN ALYSIS IN R

  16. Distrib u tion of one v ariable E XP L OR ATOR Y DATA AN ALYSIS IN R Andre w Bra y Assistant Professor , Reed College

  17. Marginal v s . conditional ggplot(cars, aes(x = hwy_mpg)) + geom_histogram() `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. Warning message: Removed 14 rows containing non-finite values (stat_bin). EXPLORATORY DATA ANALYSIS IN R

  18. Marginal v s . conditional ggplot(cars, aes(x = hwy_mpg)) + geom_histogram() + facet_wrap(~pickup) `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. Warning message: Removed 14 rows containing non-finite values (stat_bin). EXPLORATORY DATA ANALYSIS IN R

  19. B u ilding a data pipeline cars2 <- cars %>% filter(eng_size < 2.0) ggplot(cars2, aes(x = hwy_mpg)) + geom_histogram() EXPLORATORY DATA ANALYSIS IN R

  20. B u ilding a data pipeline cars %>% filter(eng_size < 2.0) %>% ggplot(aes(x = hwy_mpg)) + geom_histogram() EXPLORATORY DATA ANALYSIS IN R

  21. Filtered and faceted histogram cars %>% filter(eng_size < 2.0) %>% ggplot(aes(x = hwy_mpg)) + geom_histogram() `stat_bin()` using `bins = 30`. Pick better value with `binwidth`. EXPLORATORY DATA ANALYSIS IN R

  22. Wide bin w idth cars %>% filter(eng_size < 2.0) %>% ggplot(aes(x = hwy_mpg)) + geom_histogram(binwidth = 5) EXPLORATORY DATA ANALYSIS IN R

  23. Densit y plot cars %>% filter(eng_size < 2.0) %>% ggplot(aes(x = hwy_mpg)) + geom_density() EXPLORATORY DATA ANALYSIS IN R

  24. Wide band w idth cars %>% filter(eng_size < 2.0) %>% ggplot(aes(x = hwy_mpg)) + geom_density(bw = 5) EXPLORATORY DATA ANALYSIS IN R

  25. Let ' s practice ! E XP L OR ATOR Y DATA AN ALYSIS IN R

  26. Bo x plots E XP L OR ATOR Y DATA AN ALYSIS IN R Andre w Bra y Assistant Professor , Reed College

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  39. Side - b y- side bo x plots ggplot(common_cyl, aes(x = as.factor(ncyl), y = city_mpg)) + geom_boxplot() Warning message: Removed 11 rows containing non-finite values (stat_boxplot). EXPLORATORY DATA ANALYSIS IN R

  40. Side - b y- side bo x plots ggplot(common_cyl, aes(x = as.factor(ncyl), y = city_mpg)) + geom_boxplot() Warning message: Removed 11 rows containing non-finite values (stat_boxplot). EXPLORATORY DATA ANALYSIS IN R

  41. Side - b y- side bo x plots ggplot(common_cyl, aes(x = as.factor(ncyl), y = city_mpg)) + geom_boxplot() Warning message: Removed 11 rows containing non-finite values (stat_boxplot). EXPLORATORY DATA ANALYSIS IN R

  42. EXPLORATORY DATA ANALYSIS IN R

  43. EXPLORATORY DATA ANALYSIS IN R

  44. Let ' s practice ! E XP L OR ATOR Y DATA AN ALYSIS IN R

  45. Vis u ali z ation in higher dimensions E XP L OR ATOR Y DATA AN ALYSIS IN R Andre w Bra y Assistant Professor , Reed College

  46. Plots for 3 v ariables ggplot(cars, aes(x = msrp)) + geom_density() + facet_grid(pickup ~ rear_wheel) EXPLORATORY DATA ANALYSIS IN R

  47. Plots for 3 v ariables ggplot(cars, aes(x = msrp)) + geom_density() + facet_grid(pickup ~ rear_wheel, labeller = label_both) EXPLORATORY DATA ANALYSIS IN R

  48. Plots for 3 v ariables ggplot(cars, aes(x = msrp)) + geom_density() + facet_grid(pickup ~ rear_wheel, labeller = label_both) table(cars$rear_wheel, cars$pickup) FALSE TRUE FALSE 306 12 TRUE 98 12 EXPLORATORY DATA ANALYSIS IN R

  49. Higher dimensional plots Shape Si z e Color Pa � ern Mo v ement x- coordinate y- coordinate EXPLORATORY DATA ANALYSIS IN R

  50. Let ' s practice ! E XP L OR ATOR Y DATA AN ALYSIS IN R

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