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Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every week.
dplyr::across does not take a vector of c(mean, median) as a value to the .fns argument. Instead a list list(mean, median) is required.
Found this by coincidence, so other skripts might need some adaption as well.
Greetings
Felix
Set up poetry and organize doc structure.
mpg dataset does not exist.
You probably intended to do data("mtcars"). Similarly down below in the ui & server section.
vehicle_summary_tbl <- mpg %>%
select(class, where(is_numeric), -year) %>%
group_by(class) %>%
summarise(
across(displ:hwy, .fns = median)
) %>%
ungroup() %>%
rename(group = class) %>%
mutate_at(vars(-group), rescale)
Error in is_fun_list(.funs) : object 'rescale' not found
In addition: There were 11 warnings (use warnings() to see them)
warnings()
Warning messages:
1: Deprecated
2: Deprecated
3: Deprecated
4: Deprecated
5: Deprecated
6: Deprecated
7: Deprecated
8: Deprecated
9: Deprecated
10: Deprecated
11: Deprecated
There's an error when i run the script...
> # ggplot (2D visualization) - DS4B 101-R, Week 4
> g1 <- mtcars %>%
+ ggplot(aes(disp, mpg, color = cyl)) +
+ geom_point(size=2) +
+ scale_color_continuous(limits=c(0,8)) +
+ ggtitle("mtcars: Displacement vs mpg vs # of cylinders") +
+ theme(title = element_text(size=8),
+ text = element_text(size=12))
> # rayshader
> g1 %>%
+ plot_gg(
+ height = 3,
+ width = 3.5,
+ multicore = TRUE,
+ pointcontract = 0.7,
+ soliddepth = -200
+ )
Error in hillshade[, , 1] * scales::rescale(shadowmap, c(max_darken, 1)) :
non-conformable arrays
> g1 %>%
+ plot_gg(
+ height = 3,
+ width = 3.5,
+ multicore = TRUE,
+ pointcontract = 0.7,
+ soliddepth = -200
+ )
Error in hillshade[, , 1] * scales::rescale(shadowmap, c(max_darken, 1)) :
non-conformable arrays
> # 3D ELEVATION MATRIX ----
> volcano
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 100 100 101 101 101 101 101 100
[2,] 101 101 102 102 102 102 102 101
[...]
> volcano %>% class()
[1] "matrix" "array"
> # dplyr (data wrangling) - DS4B 101-R, Weeks 2&3
> volcano_tbl <- volcano %>%
+ as_tibble(.name_repair = "minimal") %>%
+ set_names(str_c("V", seq_along(names(.)))) %>%
+ rowid_to_column(var = "x") %>%
+ pivot_longer(
+ cols = contains("V"),
+ names_to = "y",
+ values_to = "value"
+ ) %>%
+ mutate(y = str_remove(y, "^V") %>% as.numeric())
> # ggplot (visualization) - DS4B 101-R, Week 4
> g2 <- volcano_tbl %>%
+ ggplot(aes(x = x, y = y, fill = value)) +
+ geom_tile() +
+ geom_contour(aes(z = value), color = "black") +
+ scale_x_continuous("X", expand = c(0,0)) +
+ scale_y_continuous("Y",expand = c(0,0)) +
+ scale_fill_gradientn("Z", colours = terrain.colors(10)) +
+ coord_fixed()
> g2 %>%
+ plot_gg(
+ multicore = TRUE,
+ raytrace = TRUE,
+ width = 7,
+ height = 4,
+ scale = 300,
+ windowsize = c(1400, 866),
+ zoom = 0.6,
+ phi = 30,
+ theta = 30
+ )
Error in hillshade[, , 1] * scales::rescale(shadowmap, c(max_darken, 1)) :
non-conformable arrays
In addition: Warning messages:
1: The following aesthetics were dropped during
statistical transformation: fill
ℹ This can happen when ggplot fails to infer the
correct grouping structure in the data.
ℹ Did you forget to specify a `group` aesthetic
or to convert a numerical variable into a
factor?
2: The following aesthetics were dropped during
statistical transformation: fill
ℹ This can happen when ggplot fails to infer the
correct grouping structure in the data.
ℹ Did you forget to specify a `group` aesthetic
or to convert a numerical variable into a
factor?
3: Removed 1861 rows containing missing values
(`geom_contour()`).
I don't know where to start to look for. Thanks for the help
Prepare the repo for poetry package-like structure.
The R code does not work. The function is not available in the library.
It seems the parametrization for model_prophet has changed to:
model_prophet <- prophet_reg() %>%
set_engine("prophet",yearly.seasonality=TRUE) %>%
fit(cnt ~ dteday, training(splits))
FROM:
model_prophet <- prophet_reg(
seasonality_yearly = TRUE
) %>%
set_engine("prophet") %>%
fit(cnt ~ dteday, training(splits))
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