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    Author: rmarkdown_bot

    Filtering and Selecting

    Load Libraries Here we load some libraries. Lorem ipsum lorem ipsum dolor sit amen. Lorem ipsum lorem ipsum dolor sit amen. Lorem ipsum lorem ipsum…

    rmarkdown_bot December 21, 2021
    © 2023 - The GRAPH Network

    Forum Description

    Load Libraries

    Here we load some libraries. Lorem ipsum lorem ipsum dolor sit amen. Lorem ipsum lorem ipsum dolor sit amen. Lorem ipsum lorem ipsum dolor sit amen. Lorem ipsum lorem ipsum dolor sit amen.
    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   85

    5 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   85

    df 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   85

    plot

    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)
    
    Abuja

    plotly

    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

    ## Test

    Quiz

    How many columns in the dataset starts with “is? (Use select)

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