・Code/Tools/approaches we have seen in class that you saw used over the week
From Guillaume(@G_abgrall), I found
-packages like;
library(tidyverse), library(patchwork)
-other useful functions such as,
read_csv,
-dplyr functions like;
mutate(), filter(), group_by(), summarise(), arrange()
-functions about plot editing such as;
scale_x_continuous(), geom_text(), geom_point, geom_boxplot, theme(), coord_cartesian(),
-arguments in theme functions;
plot.background, panel.background, panel.grid, axis.text, axis.ticks, axis.title, plot.margin etc
https://twitter.com/G_abgrall/status/1453743754096087041?s=20
I learned many codes and packages by week 7 and I think my skills significantly developed compared to the very beginning!
・Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class
There are also from Guillaume(@G_abgrall), I found;
-from ggplots function;
geom_moon, geom_segment, geom_area
-from dpkyr function;
ungroup()
-from theme function;
theme_light()
I noticed there are many ggplot related functions, so I would like to study more!
・Data visualizations (figures) that you enjoyed
-I like the figure from Guillaume(@G_abgrall). The reason why I like is because he used “geom_density_ridge” that we learned from week6. He tried to plot the elevation which competitors run in mountain trails. Also, the idea of Ultra-marathons in mountain and the figure that geom_density_ridge is used matches perfectly. The image is also vibrant and clear, so it is reader-friendly.
-Also, I like the image from Jamie Hudson(@Jamie_Bio). Animation is used in her image (GIF) and it is easy to understand what it says. I would like to make GIF image by R.
・Data Visualization (Figures) that could be improved (and how you would improve them)
I found the image from Jacquie Tran(@jacquietran) and it is a combination of scattering plot and boxplot. However, for me, it is difficult to understand what it says. I guess these data should be expressed by other functions such as geom_histogram().
https://twitter.com/search?q=%23tidytuesday&src=recent_search_click
・Code/Tools/approaches we have seen in class that you saw used over the week
From Guillaume(@G_abgrall), I found -packages like; library(tidyverse), library(patchwork) -other useful functions such as, read_csv, -dplyr functions like; mutate(), filter(), group_by(), summarise(), arrange() -functions about plot editing such as; scale_x_continuous(), geom_text(), geom_point, geom_boxplot, theme(), coord_cartesian(), -arguments in theme functions; plot.background, panel.background, panel.grid, axis.text, axis.ticks, axis.title, plot.margin etc https://twitter.com/G_abgrall/status/1453743754096087041?s=20
I learned many codes and packages by week 7 and I think my skills significantly developed compared to the very beginning!
・Code/Tools/approaches that you enjoyed or that surprised you that we have not seen in class
There are also from Guillaume(@G_abgrall), I found; -from ggplots function; geom_moon, geom_segment, geom_area -from dpkyr function; ungroup() -from theme function; theme_light()
I noticed there are many ggplot related functions, so I would like to study more!
・Data visualizations (figures) that you enjoyed -I like the figure from Guillaume(@G_abgrall). The reason why I like is because he used “geom_density_ridge” that we learned from week6. He tried to plot the elevation which competitors run in mountain trails. Also, the idea of Ultra-marathons in mountain and the figure that geom_density_ridge is used matches perfectly. The image is also vibrant and clear, so it is reader-friendly.
-Also, I like the image from Jamie Hudson(@Jamie_Bio). Animation is used in her image (GIF) and it is easy to understand what it says. I would like to make GIF image by R.
https://twitter.com/Jamie_Bio/status/1453437584525438981?s=20
・Data Visualization (Figures) that could be improved (and how you would improve them) I found the image from Jacquie Tran(@jacquietran) and it is a combination of scattering plot and boxplot. However, for me, it is difficult to understand what it says. I guess these data should be expressed by other functions such as geom_histogram(). https://twitter.com/search?q=%23tidytuesday&src=recent_search_click