Filtering and Selecting
Load Libraries
Here we load some libraries.
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library(tidyverse)
library(knitr)
library(highcharter)
library(plotly)
## print methods. SHould move out to optional script that is called based on parameter value
knit_print_reactable_5_rows <- function(df, options) {
df[1:5,] %>%
reactable::reactable() %>%
knitr::knit_print()
}
# registerS3method("knit_print_reactable_5_rows", "data.frame", knit_print_reactable_5_rows)
## functions
source(here::here("chapter_04_data_wrangling/utils/functions.R"))
## autograders
suppressMessages(source(here::here("chapter_04_data_wrangling/lessons/01_filtering_and_selecting_autograder.R")))
question_icon <- fontawesome::fa("fas fa-robot", fill = "purple")
cars_head <- head(cars, 5)Normal print table
cars## speed dist
## 1 4 2
## 2 4 10
## 3 7 4
## 4 7 22
## 5 8 16
## 6 9 10
## 7 10 18
## 8 10 26
## 9 10 34
## 10 11 17
## 11 11 28
## 12 12 14
## 13 12 20
## 14 12 24
## 15 12 28
## 16 13 26
## 17 13 34
## 18 13 34
## 19 13 46
## 20 14 26
## 21 14 36
## 22 14 60
## 23 14 80
## 24 15 20
## 25 15 26
## 26 15 54
## 27 16 32
## 28 16 40
## 29 17 32
## 30 17 40
## 31 17 50
## 32 18 42
## 33 18 56
## 34 18 76
## 35 18 84
## 36 19 36
## 37 19 46
## 38 19 68
## 39 20 32
## 40 20 48
## 41 20 52
## 42 20 56
## 43 20 64
## 44 22 66
## 45 23 54
## 46 24 70
## 47 24 92
## 48 24 93
## 49 24 120
## 50 25 855 rows print table
cars## speed dist
## 1 4 2
## 2 4 10
## 3 7 4
## 4 7 22
## 5 8 16
## 6 9 10
## 7 10 18
## 8 10 26
## 9 10 34
## 10 11 17
## 11 11 28
## 12 12 14
## 13 12 20
## 14 12 24
## 15 12 28
## 16 13 26
## 17 13 34
## 18 13 34
## 19 13 46
## 20 14 26
## 21 14 36
## 22 14 60
## 23 14 80
## 24 15 20
## 25 15 26
## 26 15 54
## 27 16 32
## 28 16 40
## 29 17 32
## 30 17 40
## 31 17 50
## 32 18 42
## 33 18 56
## 34 18 76
## 35 18 84
## 36 19 36
## 37 19 46
## 38 19 68
## 39 20 32
## 40 20 48
## 41 20 52
## 42 20 56
## 43 20 64
## 44 22 66
## 45 23 54
## 46 24 70
## 47 24 92
## 48 24 93
## 49 24 120
## 50 25 85df print table
cars## speed dist
## 1 4 2
## 2 4 10
## 3 7 4
## 4 7 22
## 5 8 16
## 6 9 10
## 7 10 18
## 8 10 26
## 9 10 34
## 10 11 17
## 11 11 28
## 12 12 14
## 13 12 20
## 14 12 24
## 15 12 28
## 16 13 26
## 17 13 34
## 18 13 34
## 19 13 46
## 20 14 26
## 21 14 36
## 22 14 60
## 23 14 80
## 24 15 20
## 25 15 26
## 26 15 54
## 27 16 32
## 28 16 40
## 29 17 32
## 30 17 40
## 31 17 50
## 32 18 42
## 33 18 56
## 34 18 76
## 35 18 84
## 36 19 36
## 37 19 46
## 38 19 68
## 39 20 32
## 40 20 48
## 41 20 52
## 42 20 56
## 43 20 64
## 44 22 66
## 45 23 54
## 46 24 70
## 47 24 92
## 48 24 93
## 49 24 120
## 50 25 85plot
plot(cars)
leaflet
library(leaflet)
Abuja <-
leaflet(options = leafletOptions(minZoom = 11, maxZoom = 15)) %>%
setMaxBounds(lng1 = 7.379379, lat1 = 9.122775, lng2 = 7.564087, lat2 = 9.001400) %>%
addTiles() %>%
addMarkers(lng =7.491302, lat = 9.072264, popup = "hello!") %>%
setView(lng = 7.491302, lat = 9.072264, zoom = 12)
Abujaplotly
library(plotly)
p <- ggplot(cars, aes(speed, dist)) + geom_point()
ggplotly(p)highcharter
cars$speed %>% highcharter::hchart()reactable
cars_head %>% reactable::reactable()DT
DT::datatable(cars_head)
Practice Question 5
## TestQuiz
How many columns in the dataset starts with “is? (Use select)
