Last updated: 2020-08-14
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Knit directory: r4ds_book/
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Rmd | 6c088b5 | sciencificity | 2020-08-14 | Add Chapter 1 |
Hypothesis: Cars with bigger engines use more fuel, i.e. the fuel efficiency declines as the engine size gets bigger. If miles per gallon
was on the y-axis and engine size
on the x-axis we would see a decreasing trend.
ggplot2::mpg
# A tibble: 234 x 11
manufacturer model displ year cyl trans drv cty hwy fl class
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
1 audi a4 1.8 1999 4 auto(l~ f 18 29 p comp~
2 audi a4 1.8 1999 4 manual~ f 21 29 p comp~
3 audi a4 2 2008 4 manual~ f 20 31 p comp~
4 audi a4 2 2008 4 auto(a~ f 21 30 p comp~
5 audi a4 2.8 1999 6 auto(l~ f 16 26 p comp~
6 audi a4 2.8 1999 6 manual~ f 18 26 p comp~
7 audi a4 3.1 2008 6 auto(a~ f 18 27 p comp~
8 audi a4 quat~ 1.8 1999 4 manual~ 4 18 26 p comp~
9 audi a4 quat~ 1.8 1999 4 auto(l~ 4 16 25 p comp~
10 audi a4 quat~ 2 2008 4 manual~ 4 20 28 p comp~
# ... with 224 more rows
# create coordinate system
ggplot(data = mpg, aes(x = displ,
y = hwy))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ,
y = hwy))
My hypothesis has been confirmed.
num_rows <- nrow(mtcars)
num_cols <- ncol(mtcars)
ex4_plot <- ggplot(data = mpg,
aes(x = hwy,
y = cyl)) +
geom_point()
ggplot(data = mpg)
. What do you see? aes(x = xx, y = yy)
you will see an empty canvas with the axes drawn.rows
are there in mtcars
? Columns? drv
variable describe? Ans: ‘The type of drive train, where f = front-wheel drive, r = rear wheel drive, 4 = 4wd’ex4_plot
class
versus drv
? Why is this plot not useful?ggplot(data = mpg, aes(x = class,
y = drv)) +
geom_point()
These are 2 categorical variables here so this isn’t very useful.
sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_South Africa.1252 LC_CTYPE=English_South Africa.1252
[3] LC_MONETARY=English_South Africa.1252 LC_NUMERIC=C
[5] LC_TIME=English_South Africa.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.0 purrr_0.3.4
[5] readr_1.3.1 tidyr_1.1.0 tibble_3.0.3 ggplot2_3.3.0
[9] tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.1.0 xfun_0.13 haven_2.2.0 lattice_0.20-38
[5] colorspace_1.4-1 vctrs_0.3.2 generics_0.0.2 htmltools_0.4.0
[9] yaml_2.2.1 utf8_1.1.4 rlang_0.4.7 later_1.0.0
[13] pillar_1.4.6 withr_2.2.0 glue_1.4.1 DBI_1.1.0
[17] dbplyr_1.4.3 modelr_0.1.6 readxl_1.3.1 lifecycle_0.2.0
[21] munsell_0.5.0 gtable_0.3.0 cellranger_1.1.0 rvest_0.3.5
[25] evaluate_0.14 labeling_0.3 knitr_1.28 httpuv_1.5.2
[29] fansi_0.4.1 broom_0.5.6 Rcpp_1.0.4.6 promises_1.1.0
[33] backports_1.1.6 scales_1.1.0 jsonlite_1.7.0 farver_2.0.3
[37] fs_1.4.1 hms_0.5.3 digest_0.6.25 stringi_1.4.6
[41] grid_3.6.3 rprojroot_1.3-2 cli_2.0.2 tools_3.6.3
[45] magrittr_1.5 crayon_1.3.4 whisker_0.4 pkgconfig_2.0.3
[49] ellipsis_0.3.1 xml2_1.3.2 reprex_0.3.0 lubridate_1.7.8
[53] rstudioapi_0.11 assertthat_0.2.1 rmarkdown_2.1 httr_1.4.2
[57] R6_2.4.1 nlme_3.1-144 git2r_0.26.1 compiler_3.6.3