R Notebook

library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
-- Attaching packages --------------------------------------------------------------------------------------------------------- tidyverse 1.3.0 --
v ggplot2 3.3.3     v purrr   0.3.4
v tibble  3.0.4     v dplyr   1.0.2
v tidyr   1.1.2     v stringr 1.4.0
v readr   1.4.0     v forcats 0.5.0
package 㤼㸱ggplot2㤼㸲 was built under R version 4.0.3package 㤼㸱tibble㤼㸲 was built under R version 4.0.3package 㤼㸱tidyr㤼㸲 was built under R version 4.0.2package 㤼㸱readr㤼㸲 was built under R version 4.0.3package 㤼㸱dplyr㤼㸲 was built under R version 4.0.2-- Conflicts ------------------------------------------------------------------------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

mpg

Creating a ggplot

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy))

Aesthetic Mappings

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = class))

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, size = class))

#> Warning: Using size for a discrete variable is not advised.

# Left
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, alpha = class))

# Right
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, shape = class))

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy), color = "orange")

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) + 
  facet_wrap(~ class, nrow = 2)

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) + 
  facet_grid(drv ~ cyl)

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) + 
  facet_grid(. ~ cyl)

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy))

ggplot(data = mpg) + 
  geom_smooth(mapping = aes(x = displ, y = hwy))

ggplot(data = mpg) + 
  geom_smooth(mapping = aes(x = displ, y = hwy, linetype = drv))

ggplot(data = mpg) + 
  geom_smooth(mapping = aes(x = displ, y = hwy, linetype = drv))+ geom_point(mapping = aes(x = displ, y = hwy, color=drv))

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) +
  geom_smooth(mapping = aes(x = displ, y = hwy))

ggplot(data = mpg) +
  geom_smooth(mapping = aes(x = displ, y = hwy))

              
ggplot(data = mpg) +
  geom_smooth(mapping = aes(x = displ, y = hwy, group = drv))

    
ggplot(data = mpg) +
  geom_smooth(
    mapping = aes(x = displ, y = hwy, color = drv),
    show.legend = FALSE
  )

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
  geom_point(mapping = aes(color = class)) + 
  geom_smooth()

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) + 
  geom_point(mapping = aes(color = class)) + 
  geom_smooth(data = filter(mpg, class == "subcompact"), se = FALSE)

ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = drv)) + 
  geom_point() + 
  geom_smooth(se = FALSE)

as_tibble(mpg)

tibble(
  a = lubridate::now() + runif(1e3) * 86400,
  b = lubridate::today() + runif(1e3) * 30,
  c = 1:1e3,
  d = runif(1e3),
  e = sample(letters, 1e3, replace = TRUE)
)

library(timetk)

There were 20 warnings (use warnings() to see them)

library(lubridate)

package 㤼㸱lubridate㤼㸲 was built under R version 4.0.3
Attaching package: 㤼㸱lubridate㤼㸲

The following objects are masked from 㤼㸱package:base㤼㸲:

    date, intersect, setdiff, union

taylor_30_min

interactive <- FALSE

taylor_30_min %>% 
  plot_time_series(date,value,.interactive = interactive, .plotly_slider = TRUE)

m4_daily %>% group_by(id)

m4_daily %>%
  group_by(id) %>%
  plot_time_series(date, value, 
                   .facet_ncol = 2, .facet_scales = "free",
                   .interactive = interactive)

m4_hourly %>% group_by(id)

m4_hourly %>%
  group_by(id) %>%
  plot_time_series(date, log(value),             # Apply a Log Transformation
                   .color_var = week(date),      # Color applied to Week transformation
                   # Facet formatting
                   .facet_ncol = 2, 
                   .facet_scales = "free", 
                   .interactive = interactive)

taylor_30_min %>%
  plot_time_series(date, value, 
                   .color_var = month(date, label = TRUE),
                   
                   # Returns static ggplot
                   .interactive = FALSE,  
                   
                   # Customization
                   .title = "Taylor's MegaWatt Data",
                   .x_lab = "Date (30-min intervals)",
                   .y_lab = "Energy Demand (MW)",
                   .color_lab = "Month") +
  scale_y_continuous(labels = scales::comma_format())