Diamonds viz

Diamonds Viz

Let’s plot the diamonds dataset using ggplot2.

#load libraries
library(ggplot2)

Let’s take a quick look at the data.

head(diamonds)

# A tibble: 6 × 10
  carat cut       color clarity depth table price     x     y     z
  <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
1  0.23 Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
2  0.21 Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
3  0.23 Good      E     VS1      56.9    65   327  4.05  4.07  2.31
4  0.29 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
5  0.31 Good      J     SI2      63.3    58   335  4.34  4.35  2.75
6  0.24 Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48

View the diamonds dataset as counts by ::: {.callout}

ggplot(data = diamonds,
   aes(x = cut, y = price))+
geom_histogram( stat = "identity")

Warning in geom_histogram(stat = "identity"): Ignoring unknown parameters:
`binwidth`, `bins`, and `pad`

Let’s log the date and time.

library(lubridate)

Attaching package: 'lubridate'

The following objects are masked from 'package:base':

    date, intersect, setdiff, union

my_time <- now(tzone = "America/Vancouver")
my_time

[1] "2024-09-19 12:08:47 PDT"